Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities

Purpose: To examine rural–urban differences in motor vehicle fatality (MVF) risk factors. Methods: We used 2017 County Health Rankings data to run stratified regression models to estimate county-level correlates of motor vehicle fatalities (MVFs) by rural and urban location. Results: Rural counties...

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Detalles Bibliográficos
Autores principales: Henning-Smith, Carrie, Kozhimannil, Katy B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2018
Materias:
Short Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167004/
https://www.ncbi.nlm.nih.gov/pubmed/30283875
http://dx.doi.org/10.1089/heq.2018.0006
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author Henning-Smith, Carrie
Kozhimannil, Katy B.
author_facet Henning-Smith, Carrie
Kozhimannil, Katy B.
author_sort Henning-Smith, Carrie
collection PubMed
description Purpose: To examine rural–urban differences in motor vehicle fatality (MVF) risk factors. Methods: We used 2017 County Health Rankings data to run stratified regression models to estimate county-level correlates of motor vehicle fatalities (MVFs) by rural and urban location. Results: Rural counties have higher rates of MVFs than urban counties (22 vs. 14 per 100,000, p<0.001). Physical inactivity and uninsurance were associated with higher rates of MVFs, as was having a more racially or ethnically concentrated population and larger percentages of younger or older adults. Conclusion: Interventions to reduce MVFs should take geographic location and population composition into account.
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spelling pubmed-61670042018-10-03 Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities Henning-Smith, Carrie Kozhimannil, Katy B. Health Equity Short Report Purpose: To examine rural–urban differences in motor vehicle fatality (MVF) risk factors. Methods: We used 2017 County Health Rankings data to run stratified regression models to estimate county-level correlates of motor vehicle fatalities (MVFs) by rural and urban location. Results: Rural counties have higher rates of MVFs than urban counties (22 vs. 14 per 100,000, p<0.001). Physical inactivity and uninsurance were associated with higher rates of MVFs, as was having a more racially or ethnically concentrated population and larger percentages of younger or older adults. Conclusion: Interventions to reduce MVFs should take geographic location and population composition into account. Mary Ann Liebert, Inc., publishers 2018-09-25 /pmc/articles/PMC6167004/ /pubmed/30283875 http://dx.doi.org/10.1089/heq.2018.0006 Text en © Carrie Henning-Smith and Katy B. Kozhimannil 2018; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Short Report
Henning-Smith, Carrie
Kozhimannil, Katy B.
Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title_full Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title_fullStr Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title_full_unstemmed Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title_short Rural–Urban Differences in Risk Factors for Motor Vehicle Fatalities
title_sort rural–urban differences in risk factors for motor vehicle fatalities
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167004/
https://www.ncbi.nlm.nih.gov/pubmed/30283875
http://dx.doi.org/10.1089/heq.2018.0006
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