Evidence map›Paper›PMID 33881409›Full record

ArticleJMIR public health and surveillance2021

Association of Opioid Use Disorder With 2016 Presidential Voting Patterns: Cross-sectional Study in New York State at Census Tract Level.

Anthony Xiang, Wei Hou, Sina Rashidian, Richard N Rosenthal, Kayley Abell-Hart, Xia Zhao, Fusheng Wang

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Anthony Xiang *Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0003-1441-969X
Wei Hou *Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-1658-8895
Sina RashidianStony Brook University, Stony Brook, NY, United States.ORCID 0000-0003-1210-2939
Richard N Rosenthal *Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-6011-809X
Kayley Abell-HartStony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-3887-8025
Xia ZhaoStony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-9056-6221
Fusheng WangStony Brook University, Stony Brook, NY, United States.ORCID 0000-0002-9369-9361
Stony Brook University · USStony Brook School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOpioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD).

objectiveWe aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State.

methodsThis cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one OUD diagnosis between 2010 and 2016 and 36,004 patients with at least one OP diagnosis between 2012 and 2016. Geospatial mappings were created to compare areas of New York in OUD rates and presidential voting patterns. A multiple regression model examines the extent that certain factors explain OUD rate variation.

resultsSeveral areas shared similar patterns of OUD rates and Republican vote: census tracts in western New York, central New York, and Suffolk County. The correlation between OUD rates and the Republican vote was .38 (P<.001). The regression model with census tract level of demographic and socioeconomic factors explains 30% of the variance in OUD rates, with disability and Republican vote as the most significant predictors.

conclusionsAt the census tract level, OUD rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic despair-related features explain a large portion of the association between the Republican vote and OUD. Together, these findings underscore the importance of socioeconomic interventions in combating the opioid epidemic.

Indexed as

PoliticsAdolescentAdultAgedCensusesCross-Sectional StudiesFemaleHumansMaleMiddle AgedNew YorkOpioid-Related DisordersYoung Adultgeographic varianceopioid poisoningopioid use disorderpresidential electionracial and ethnic disparitiessociodemographic factors

Identifiers

PMID33881409
PMCPMC8100884
OpenAlexW3131932834

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.