President-elect Donald Trump won a stunning electoral victory thanks to triumphs in several states that had long swung Democratic, like Pennsylvania, Wisconsin, and Michigan, as well as swing states, like Ohio and Florida.
Since the election, Shannon Monnat, a rural sociologist and demographer at Pennsylvania State University, has dug into the voting data to try to figure out why Trump “overperformed” in certain counties.
Through her research, which was released in a brief Monday, Monnat found a possible answer: Counties that voted more heavily for Trump than expected were closely correlated with counties that experienced high rates of death caused by drugs, alcohol, and suicide.
Monnat wasn’t surprised by the correlation.
“I expected to see it because when you think about the underlying factors that lead to overdose or suicide, it’s depression, despair, distress, and anxiety,” she told Business Insider in November. “That was the message that Trump was appealing to.”
That wasn’t the only correlation Monnat found. Here’s what else she saw:
Trump outperformed 2012 Republican candidate Mitt Romney in counties across the US that experienced higher rates of mortality related to drugs, alcohol, or suicide.
Trump’s overperformance was more pronounced in the industrial Midwest – which consists of Illinois, Indiana, Michigan, Ohio, Pennsylvania, and Wisconsin – and New England.
In the industrial Midwest, Trump did better than Romney by an average of 16.7 percentage points, compared with only 8.1 points in counties with the lowest mortality rates, according to Monnat.
In New England, Trump did worse than Romney by 3.1 points in the counties with the lowest mortality rates, compared with doing better by nearly 10 points in the counties with the highest mortality rates.
Many of those counties with high drug-, alcohol-, and suicide-related mortality rates have been hard hit by the opioid crisis in recent years. Ohio, Pennsylvania, Indiana, New Hampshire, and West Virginia are considered to be some of the states hardest hit by heroin- and opioid-related overdose deaths.
Monnat noted that counties that were more “economically distressed” swung more heavily to Trump than expected, as well.
A major correlation Monnat discovered was that counties ranked highly on her “economic distress index” had a high number of working-class people who voted more heavily for Trump than they did for Romney in 2012.
The index, which Monnat has used in her research for years, combines the percentages of people who are in poverty, unemployed, disabled, in single-parent families, living on public assistance, or living without health insurance.
Though Monnat said she expected this correlation in the industrial Midwest, which has been hard hit by globalization and losses in manufacturing jobs, the correlation was strong in New England as well.
Monnat told Business Insider in November that high mortality rates were not enough to explain why people voted for Trump but were “reflective of the structural problem.”
In Monnat’s most recent research, she found a strong link between counties affected by economic distress, high numbers of working-class people, and high rates of drug-, alcohol-, and suicide-related mortality.
Counties with high rates of drug-, alcohol-, and suicide-related mortality invariably correlated with counties of high economic distress, whether that county was located in a metropolitan area or not. The same held true for high numbers of working-class people, though that correlation was not as pronounced, she said.
“These findings reflect larger systemic economic and social problems that go far beyond drug and alcohol abuse and suicide,” Monnat wrote. “In many of the counties where Trump did the best, economic precarity has been building and social and family networks have been breaking down for several decades.”
According to Monnat, “bifurcation” is occurring in the industrial Midwest and New England.
“In New England, there is a clear bifurcation between counties with low economic distress, low mortality rates, and poor Trump performance versus counties with high economic distress, high mortality rates, and strong Trump performance,” she wrote.
Monnat said the bifurcation was similar in the industrial Midwest, though it was not as pronounced. In Appalachia, Trump appeared to perform better in the least economically distressed counties with high mortality. Monnat suggested that this may be because so much of Appalachia is economically distressed – and as has been for decades.
Monnat said none of the relationships she identified should be seen as causal, because no single factor could explain a complex election outcome. Instead, Monnat suggested that the analyses demonstrate the outsize role that “community-level well-being” played in the election, as well as context for the state of the communities that many credit with swinging the election.
Monnat wasn’t the only one to notice a powerful voting correlation.
- Jonathan Drake/Reuters