Evidence map›Paper›PMID 30646079›Full record

ArticleJAMA network open2018

Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016.

James S Goodwin, Yong-Fang Kuo, David Brown, David Juurlink, Mukaila Raji

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
9.9field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 62 citations in OpenAlex.

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  14. Time Trends in Opioid Use by Dementia Severity in Long-Term Care Nursing Home Residents.Journal of the American Medical Directors Association · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

James S GoodwinDepartment of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston.
Yong-Fang KuoDepartment of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston.
David BrownUniversity of Texas Medical Branch, Galveston.
David JuurlinkDepartment of Medicine, University of Toronto, Toronto, Ontario, Canada.
Mukaila RajiDepartments of Medicine, University of Texas Medical Branch, Galveston.
The University of Texas Medical Branch at Galveston · USUniversity of Toronto · CA

Funding

Pattern, Variation and Outcomes of Opioid Prescription in Older AdultsR01DA039192 · NIDA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI KUO, YONG-FANG, RAJI, MUKAILA A · 2016 to 2023
$3.1M
Established Investigator Award in Cancer Prevention & ControlK05CA134923 · NCI · UNIVERSITY OF TEXAS MED BR GALVESTON · PI GOODWIN, MD, JAMES S. · 2008 to 2019
$1.0M
NCI NIH HHS K05 CA134923NIDA NIH HHS R01 DA039192
6 · The paper itself

Abstract

Importance: The causes of the opioid epidemic are incompletely understood. Objective: To explore the overlap between the geographic distribution of US counties with high opioid use and the vote for the Republican candidate in the 2016 presidential election. Design, Setting, and Participants: A cross-sectional analysis to explore the extent to which individual- and county-level demographic and economic measures explain the association of opioid use with the 2016 presidential vote at the county level, using rate of prescriptions for at least a 90-day supply of opioids in 2015. Medicare Part D enrollees (N = 3 764 361) constituting a 20% national sample were included. Main Outcomes and Measures: Chronic opioid use was measured by county rate of receiving a 90-day or greater supply of opioids prescribed in 2015. Results: Of the 3 764 361 Medicare Part D enrollees in the 20% sample, 679 314 (18.0%) were younger than 65 years, 2 283 007 (60.6%) were female, 3 053 688 (81.1%) were non-Hispanic white, 351 985 (9.3%) were non-Hispanic black, and 198 778 (5.3%) were Hispanic. In a multilevel analysis including county and enrollee, the county of residence explained 9.2% of an enrollee's odds of receiving prolonged opioids after adjusting for individual enrollee characteristics. The correlation between a county's Republican presidential vote and the adjusted rate of Medicare Part D recipients receiving prescriptions for prolonged opioid use was 0.42 (P < .001). In the 693 counties with adjusted rates of opioid prescription significantly higher than the mean county rate, the mean (SE) Republican presidential vote was 59.96% (1.73%), vs 38.67% (1.15%) in the 638 counties with significantly lower rates. Adjusting for county-level socioeconomic measures in linear regression models explained approximately two-thirds of the association of opioid rates and presidential voting rates. Conclusions and Relevance: Support for the Republican candidate in the 2016 election is a marker for physical conditions, economic circumstances, and cultural forces associated with opioid use. The commonly used socioeconomic indicators do not totally capture all of those forces.

Indexed as

Medicare Part DPoliticsAdultAnalgesics, OpioidCross-Sectional StudiesDatabases, FactualFemaleGeographyHumansLocal GovernmentMaleMiddle AgedMultilevel AnalysisOpioid-Related DisordersPrescriptionsSocioeconomic FactorsAnalgesics, Opioid

Identifiers

PMID30646079
PMCPMC6324412
OpenAlexW2808911855

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.