Independent Relationship of Changes in Death Rates with Changes in US Presidential Voting.


Journal

Journal of general internal medicine
ISSN: 1525-1497
Titre abrégé: J Gen Intern Med
Pays: United States
ID NLM: 8605834

Informations de publication

Date de publication:
03 2019
Historique:
received: 11 01 2018
accepted: 28 06 2018
revised: 16 05 2018
pubmed: 7 9 2018
medline: 14 8 2020
entrez: 7 9 2018
Statut: ppublish

Résumé

The outcome of the 2016 presidential election is commonly attributed to socioeconomic and ethnic/racial issues, but health issues, including "deaths of despair," may also have contributed. To assess whether changes in age-adjusted death rates were independently associated with changes in presidential election voting in 2016 vs. 2008. We used publicly available data in each of 3112 US counties to correlate changes in a county's presidential voting in 2016 compared with 2008 with recent changes in its age-adjusted death rate, after controlling for population and rural-urban status, median age, race/ethnicity, income, education, unemployment rate, and health insurance rate. Cross-sectional analysis of county-specific data. All 3112 US counties. The independent correlation of a county's change in age-adjusted death rate between 2000 and 2015 with its net percentage Republican gain or loss in the presidential election of 2016 vs. 2008. In 2016, President Trump increased the Republican presidential vote percentage in 83.8% of counties compared with Senator McCain in 2008. Counties with an increased Republican vote percentage in 2016 vs. 2008 had a 15% higher 2015 age-adjusted death rate than counties with an increased Democratic vote percentage. Since 2000, overall death rates declined by less than half as much, and death rates from drugs, alcohol, and suicide increased 2.5 times as much in counties with Republican gains compared with counties with Democratic gains. In multivariable analyses, Republican net presidential gain in 2016 vs. 2008 was independently correlated with slower reductions in a county's age-adjusted death rate. Although correlation cannot infer causality, modest reductions in death rates might theoretically have shifted Pennsylvania, Michigan, and Wisconsin to Secretary Clinton. Less of a reduction in age-adjusted death rates was an independent correlate of an increased Republican percentage vote in 2016 vs. 2008. Death rates may be markers of dissatisfactions and fears that influenced the 2016 Presidential election outcomes.

Sections du résumé

BACKGROUND
The outcome of the 2016 presidential election is commonly attributed to socioeconomic and ethnic/racial issues, but health issues, including "deaths of despair," may also have contributed.
OBJECTIVE
To assess whether changes in age-adjusted death rates were independently associated with changes in presidential election voting in 2016 vs. 2008.
DESIGN
We used publicly available data in each of 3112 US counties to correlate changes in a county's presidential voting in 2016 compared with 2008 with recent changes in its age-adjusted death rate, after controlling for population and rural-urban status, median age, race/ethnicity, income, education, unemployment rate, and health insurance rate.
DESIGN SETTING
Cross-sectional analysis of county-specific data.
SETTING/PARTICIPANTS
All 3112 US counties.
MAIN MEASURES
The independent correlation of a county's change in age-adjusted death rate between 2000 and 2015 with its net percentage Republican gain or loss in the presidential election of 2016 vs. 2008.
KEY RESULTS
In 2016, President Trump increased the Republican presidential vote percentage in 83.8% of counties compared with Senator McCain in 2008. Counties with an increased Republican vote percentage in 2016 vs. 2008 had a 15% higher 2015 age-adjusted death rate than counties with an increased Democratic vote percentage. Since 2000, overall death rates declined by less than half as much, and death rates from drugs, alcohol, and suicide increased 2.5 times as much in counties with Republican gains compared with counties with Democratic gains. In multivariable analyses, Republican net presidential gain in 2016 vs. 2008 was independently correlated with slower reductions in a county's age-adjusted death rate. Although correlation cannot infer causality, modest reductions in death rates might theoretically have shifted Pennsylvania, Michigan, and Wisconsin to Secretary Clinton.
CONCLUSIONS
Less of a reduction in age-adjusted death rates was an independent correlate of an increased Republican percentage vote in 2016 vs. 2008. Death rates may be markers of dissatisfactions and fears that influenced the 2016 Presidential election outcomes.

Identifiants

pubmed: 30187378
doi: 10.1007/s11606-018-4568-6
pii: 10.1007/s11606-018-4568-6
pmc: PMC6420486
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

363-371

Subventions

Organisme : NIA NIH HHS
ID : R01 AG054466
Pays : United States
Organisme : NIEHS NIH HHS
ID : P30 ES009089
Pays : United States

Commentaires et corrections

Type : CommentIn
Type : CommentIn
Type : CommentIn

Références

JAMA. 2016 Dec 13;316(22):2385-2401
pubmed: 27959996
Ann N Y Acad Sci. 2010 Feb;1186:56-68
pubmed: 20201868
Proc Natl Acad Sci U S A. 2015 Dec 8;112(49):15078-83
pubmed: 26575631
Am J Public Health. 2017 Oct;107(10):1560-1562
pubmed: 28817322
JAMA. 2018 Mar 13;319(10):1013-1023
pubmed: 29536097
Am J Public Health. 2017 Oct;107(10):1541-1547
pubmed: 28817333
JAMA. 2016 Apr 26;315(16):1750-66
pubmed: 27063997
Ann Intern Med. 2017 Sep 19;167(6):424-431
pubmed: 28655034
Soc Sci Med. 2018 Jan;197:33-38
pubmed: 29220706
N Engl J Med. 2017 Aug 10;377(6):586-593
pubmed: 28636831
PLoS One. 2017 Oct 2;12(10):e0185051
pubmed: 28968415
PLoS One. 2018 Apr 25;13(4):e0194308
pubmed: 29694402
Natl Vital Stat Rep. 2017 Nov;66(6):1-75
pubmed: 29235985
NCHS Data Brief. 2017 Dec;(294):1-8
pubmed: 29319475
Int J Epidemiol. 2018 Feb 1;47(1):81-88
pubmed: 29040539
Am J Public Health. 2017 Jan;107(1):130-135
pubmed: 27854531
Epidemiology. 2010 Jul;21 Suppl 4:S51-7
pubmed: 20220524
NCHS Data Brief. 2017 Dec;(293):1-8
pubmed: 29319473
Proc Natl Acad Sci U S A. 2003 Sep 16;100(19):11176-83
pubmed: 12958207
Circulation. 2018 Jun 19;137(25):2686-2688
pubmed: 29915094
Lancet. 2017 Mar 11;389(10073):1043-1054
pubmed: 28131493
JAMA Intern Med. 2017 Jul 1;177(7):1003-1011
pubmed: 28492829
Proc Natl Acad Sci U S A. 2010 Dec 28;107(52):22463-8
pubmed: 21149705

Auteurs

Lee Goldman (L)

Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA. lgoldman@columbia.edu.
Mailman School of Public Health, Columbia University, New York, NY, USA. lgoldman@columbia.edu.

Maribel P Lim (MP)

Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.

Qixuan Chen (Q)

Mailman School of Public Health, Columbia University, New York, NY, USA.

Peng Jin (P)

Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.

Peter Muennig (P)

Mailman School of Public Health, Columbia University, New York, NY, USA.

Andrew Vagelos (A)

Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.

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