14. 8. Read the story below from NPR and then identify the veryimportant concept . How does it relate to correlation andChi-Square
Analysis Finds Geographic Overlap In Opioid Use And TrumpSupport In 2016
June 23, 20188:02 AM ET
Paul Chisholm, NPR
In 2016, Donald Trump captured 68 percent of the vote in WestVirginia, a state hit hard by opioid overdoses.
BRENDAN SMIALOWSKI/AFP/Getty Images
The fact that rural, economically disadvantaged parts of thecountry broke heavily for the Republican candidate in the 2016election is well known. But Medicare data indicate that voters inareas that went for Trump weren't just hurting economically — manyof them were receiving prescriptions for opioid painkillers.
The findings were published Friday in the medical journalJAMA Network Open. Researchers found a geographicrelationship between support for Trump and prescriptions for opioidpainkillers.
It's easy to see similarities between the places hardest hit bythe opioid epidemic and a map of Trump strongholds. \"When we lookat the two maps, there was a clear overlap between counties thathad high opioid use ... and the vote for Donald Trump,\" says Dr.James S. Goodwin, chair of geriatrics at the University of TexasMedical Branch in Galveston and the study's lead author. \"Therewere blogs from various people saying there was this overlap. Butwe had national data.\"
Goodwin and his team looked at data from Census Bureau, the 2016election and Medicare Part D, a prescription drug program thatserves the elderly and disabled.
To estimate the prevalence of opioid use by county, theresearchers used the percentage of enrollees who had receivedprescriptions for a three-month or longer supply of opioids.Goodwin says that prescription opioid use is strongly correlatedwith illicit opioid use, which can be hard to quantify.
\"There are very inexact ways of measuring illegal opioid use,\"Goodwin says. \"All we can really measure with precision is legalopioid use.\"
Goodwin's team examined how a variety of factors could haveinfluenced each county's rate of chronic opioid prescriptions.After correcting for demographic variables such as age and race,Goodwin found that support for Trump in the 2016 election closelytracked opioid prescriptions.
In counties with higher-than-average rates of chronic opioidprescriptions, 60 percent of the voters went for Trump. In thecounties with lower-than-average rates, only 39 percent voted forTrump.
A lot of this disparity could be chalked up to social factorsand economic woes. Rural, economically-depressed counties wentstrongly for Trump in the 2016 election. These are the same placeswhere opioid use is prevalent. As a result, opioid use and supportfor Trump might not be directly related, but rather two symptoms ofthe same problem – a lack of economic opportunity.
To test this theory, Goodwin included other county-level factorsin the analysis. These included factors such as unemployment rate,median income, how rural they are, education level, and religiousservice attendance, among others.
These socioeconomic variables accounted for about two-thirds ofthe link between voter support for Trump and opioid rates, thepaper's authors write. However, socioeconomic factors didn'texplain all of the correlation seen in the study.
\"It very well may be that if you're in a county that isdissolving because of opioids, you're looking around and you'reseeing ruin. That can lead to a sense of despair,\" Goodwin says.\"You want something different. You want radical change.\"
For voters in communities hit hard by the opioid epidemic, theunconventional Trump candidacy may have been the change people werelooking for, Goodwin says.
Dr. Nancy E. Morden, associate professor at the DartmouthInstitute for Health Policy and Clinical Practice, agrees. \"Peoplewho reach for an opioid might also reach for ... near-term fixes,\"she says. \"I think that Donald Trump's campaign was a promise fornear-term relief.\"
Goodwin's study has limitations and can't establish that opioiduse was a definitive factor in how people voted.
\"With that kind of study design, you have to be cautious interms of drawing any causal conclusions,\" cautions EleneKennedy-Hendricks, an assistant scientist in the Department ofHealth Policy and Management at the Johns Hopkins Bloomberg Schoolof Public Health. \"The directionality is complicated.\"
Goodwin acknowledges that the study has shortcomings.
\"We were not implying causality, that the Trump vote causedopioids or that opioids caused the Trump vote,\" he cautions. \"We'retalking about associations.\"
Still, the study serves as an interesting example highlightingthe links between economic opportunity, social issues and politicalbehavior.
\"The types of discussions around what drove the '16 election,and the forces that were behind that, should also be included whenpeople are talking about the opioid epidemic,\" Goodwin says.
