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Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324412/ https://www.ncbi.nlm.nih.gov/pubmed/30646079 http://dx.doi.org/10.1001/jamanetworkopen.2018.0450 |
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author | Goodwin, James S. Kuo, Yong-Fang Brown, David Juurlink, David Raji, Mukaila |
author_facet | Goodwin, James S. Kuo, Yong-Fang Brown, David Juurlink, David Raji, Mukaila |
author_sort | Goodwin, James S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6324412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Medical Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-63244122019-01-22 Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 Goodwin, James S. Kuo, Yong-Fang Brown, David Juurlink, David Raji, Mukaila JAMA Netw Open Original Investigation 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. American Medical Association 2018-06-22 /pmc/articles/PMC6324412/ /pubmed/30646079 http://dx.doi.org/10.1001/jamanetworkopen.2018.0450 Text en Copyright 2018 Goodwin JS et al. JAMA Network Open. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the CC-BY License. |
spellingShingle | Original Investigation Goodwin, James S. Kuo, Yong-Fang Brown, David Juurlink, David Raji, Mukaila Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title | Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title_full | Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title_fullStr | Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title_full_unstemmed | Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title_short | Association of Chronic Opioid Use With Presidential Voting Patterns in US Counties in 2016 |
title_sort | association of chronic opioid use with presidential voting patterns in us counties in 2016 |
topic | Original Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324412/ https://www.ncbi.nlm.nih.gov/pubmed/30646079 http://dx.doi.org/10.1001/jamanetworkopen.2018.0450 |
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