Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender
► Mixed logit models capture population heterogeneity in injury severity. ► Age and gender lead to important population heterogeneity effects. ► Transportation policy must account for increased aging-related population variance. ► Population move towards newer safer vehicles can have a significant s...
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| Veröffentlicht in: | Accident analysis and prevention 2013-01, Vol.50, p.1073-1081 |
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| container_title | Accident analysis and prevention |
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| creator | Kim, Joon-Ki Ulfarsson, Gudmundur F. Kim, Sungyop Shankar, Venkataraman N. |
| description | ► Mixed logit models capture population heterogeneity in injury severity. ► Age and gender lead to important population heterogeneity effects. ► Transportation policy must account for increased aging-related population variance. ► Population move towards newer safer vehicles can have a significant safety benefit. ► Key safety benefits from reduced drunk driving, improved street lighting.
This research develops a mixed logit model of driver-injury severity in single-vehicle crashes in California. The research especially considers the heterogeneous effects of age and gender. Older drivers (65+ years old) were found to have a random parameter with about half the population having a higher probability of a fatal injury given a crash than the comparison group of 25–64 year olds with all other factors than age kept constant. The other half of the 65+ population had a lower probability of fatal injury. Heterogeneity was also noted in vehicle age, but related to the gender of the driver, with males linked to, on average, a higher probability of fatal injury in a newer vehicle compared with females, all other factors kept constant. These effects lend support to the use of mixed logit models in injury severity research and show age and gender based population heterogeneity.
Several other factors were found to significantly increase the probability of fatal injury for drivers in single-vehicle crashes, most notably: male driver, drunk driving, unsafe speed, older driver (65+) driving an older vehicle, and darkness without streetlights. |
| doi_str_mv | 10.1016/j.aap.2012.08.011 |
| format | Article |
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This research develops a mixed logit model of driver-injury severity in single-vehicle crashes in California. The research especially considers the heterogeneous effects of age and gender. Older drivers (65+ years old) were found to have a random parameter with about half the population having a higher probability of a fatal injury given a crash than the comparison group of 25–64 year olds with all other factors than age kept constant. The other half of the 65+ population had a lower probability of fatal injury. Heterogeneity was also noted in vehicle age, but related to the gender of the driver, with males linked to, on average, a higher probability of fatal injury in a newer vehicle compared with females, all other factors kept constant. These effects lend support to the use of mixed logit models in injury severity research and show age and gender based population heterogeneity.
Several other factors were found to significantly increase the probability of fatal injury for drivers in single-vehicle crashes, most notably: male driver, drunk driving, unsafe speed, older driver (65+) driving an older vehicle, and darkness without streetlights.</description><identifier>ISSN: 0001-4575</identifier><identifier>EISSN: 1879-2057</identifier><identifier>DOI: 10.1016/j.aap.2012.08.011</identifier><identifier>PMID: 22939394</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Accidents, Traffic - statistics & numerical data ; Adult ; Age ; Age Factors ; Aged ; Automobile Driving ; Biological and medical sciences ; California - epidemiology ; Female ; Gender ; Heterogeneity ; Humans ; Injury severity ; Injury Severity Score ; Logistic Models ; Male ; Medical sciences ; Middle Aged ; Miscellaneous ; Mixed logit ; Prevention and actions ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Risk Factors ; Sex Factors ; Single-vehicle</subject><ispartof>Accident analysis and prevention, 2013-01, Vol.50, p.1073-1081</ispartof><rights>2012 Elsevier Ltd</rights><rights>2014 INIST-CNRS</rights><rights>Copyright © 2012 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c444t-cae36e5958f6da6e859c242bd63ab4849624a41f8da4f732c01c7ce703046f013</citedby><cites>FETCH-LOGICAL-c444t-cae36e5958f6da6e859c242bd63ab4849624a41f8da4f732c01c7ce703046f013</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.aap.2012.08.011$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27090528$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22939394$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Joon-Ki</creatorcontrib><creatorcontrib>Ulfarsson, Gudmundur F.</creatorcontrib><creatorcontrib>Kim, Sungyop</creatorcontrib><creatorcontrib>Shankar, Venkataraman N.</creatorcontrib><title>Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender</title><title>Accident analysis and prevention</title><addtitle>Accid Anal Prev</addtitle><description>► Mixed logit models capture population heterogeneity in injury severity. ► Age and gender lead to important population heterogeneity effects. ► Transportation policy must account for increased aging-related population variance. ► Population move towards newer safer vehicles can have a significant safety benefit. ► Key safety benefits from reduced drunk driving, improved street lighting.
This research develops a mixed logit model of driver-injury severity in single-vehicle crashes in California. The research especially considers the heterogeneous effects of age and gender. Older drivers (65+ years old) were found to have a random parameter with about half the population having a higher probability of a fatal injury given a crash than the comparison group of 25–64 year olds with all other factors than age kept constant. The other half of the 65+ population had a lower probability of fatal injury. Heterogeneity was also noted in vehicle age, but related to the gender of the driver, with males linked to, on average, a higher probability of fatal injury in a newer vehicle compared with females, all other factors kept constant. These effects lend support to the use of mixed logit models in injury severity research and show age and gender based population heterogeneity.
Several other factors were found to significantly increase the probability of fatal injury for drivers in single-vehicle crashes, most notably: male driver, drunk driving, unsafe speed, older driver (65+) driving an older vehicle, and darkness without streetlights.</description><subject>Accidents, Traffic - statistics & numerical data</subject><subject>Adult</subject><subject>Age</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Automobile Driving</subject><subject>Biological and medical sciences</subject><subject>California - epidemiology</subject><subject>Female</subject><subject>Gender</subject><subject>Heterogeneity</subject><subject>Humans</subject><subject>Injury severity</subject><subject>Injury Severity Score</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Miscellaneous</subject><subject>Mixed logit</subject><subject>Prevention and actions</subject><subject>Public health. 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Hygiene-occupational medicine</subject><subject>Risk Factors</subject><subject>Sex Factors</subject><subject>Single-vehicle</subject><issn>0001-4575</issn><issn>1879-2057</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU2P0zAQhi0EYsvCD-CCfEHikuzYcewETqvyKa3EZfdsTe1J6ypNip1U9MB_X1ctcAP5YI39zDuWH8ZeCygFCH2zLRH3pQQhS2hKEOIJW4jGtIWE2jxlCwAQhapNfcVepLTNpWlM_ZxdSdlWeakF-_UxhgPFIgzbOR55olyE6cjDwFMY1j0VB9oE1xN3EdOG0ulmiX3oxjgEfM9v-S78JM_7cR0mjgP2xxQSHzu-oYniuKaBToF-Jj6NHNeUIc_zsaf4kj3rsE_06rJfs4fPn-6XX4u771--LW_vCqeUmgqHVGmq27rptEdNTd06qeTK6wpXqlGtlgqV6BqPqjOVdCCccWSgAqU7ENU1e3fO3cfxx0xpsruQHPU9DjTOyQqtQYlaG_N_VEqRJ0rQGRVn1MUxpUid3ceww3i0AuxJkN3aLMieBFlobBaUe95c4ufVjvyfjt9GMvD2AmBy2HcRBxfSX85AC7VsMvfhzFH-t0OgaJMLNDjyIZKbrB_DP57xCEUErgk</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Kim, Joon-Ki</creator><creator>Ulfarsson, Gudmundur F.</creator><creator>Kim, Sungyop</creator><creator>Shankar, Venkataraman N.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7T2</scope><scope>7U2</scope><scope>C1K</scope></search><sort><creationdate>201301</creationdate><title>Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender</title><author>Kim, Joon-Ki ; Ulfarsson, Gudmundur F. ; Kim, Sungyop ; Shankar, Venkataraman N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c444t-cae36e5958f6da6e859c242bd63ab4849624a41f8da4f732c01c7ce703046f013</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Accidents, Traffic - statistics & numerical data</topic><topic>Adult</topic><topic>Age</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Automobile Driving</topic><topic>Biological and medical sciences</topic><topic>California - epidemiology</topic><topic>Female</topic><topic>Gender</topic><topic>Heterogeneity</topic><topic>Humans</topic><topic>Injury severity</topic><topic>Injury Severity Score</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Miscellaneous</topic><topic>Mixed logit</topic><topic>Prevention and actions</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Risk Factors</topic><topic>Sex Factors</topic><topic>Single-vehicle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Joon-Ki</creatorcontrib><creatorcontrib>Ulfarsson, Gudmundur F.</creatorcontrib><creatorcontrib>Kim, Sungyop</creatorcontrib><creatorcontrib>Shankar, Venkataraman N.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Accident analysis and prevention</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Joon-Ki</au><au>Ulfarsson, Gudmundur F.</au><au>Kim, Sungyop</au><au>Shankar, Venkataraman N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender</atitle><jtitle>Accident analysis and prevention</jtitle><addtitle>Accid Anal Prev</addtitle><date>2013-01</date><risdate>2013</risdate><volume>50</volume><spage>1073</spage><epage>1081</epage><pages>1073-1081</pages><issn>0001-4575</issn><eissn>1879-2057</eissn><abstract>► Mixed logit models capture population heterogeneity in injury severity. ► Age and gender lead to important population heterogeneity effects. ► Transportation policy must account for increased aging-related population variance. ► Population move towards newer safer vehicles can have a significant safety benefit. ► Key safety benefits from reduced drunk driving, improved street lighting.
This research develops a mixed logit model of driver-injury severity in single-vehicle crashes in California. The research especially considers the heterogeneous effects of age and gender. Older drivers (65+ years old) were found to have a random parameter with about half the population having a higher probability of a fatal injury given a crash than the comparison group of 25–64 year olds with all other factors than age kept constant. The other half of the 65+ population had a lower probability of fatal injury. Heterogeneity was also noted in vehicle age, but related to the gender of the driver, with males linked to, on average, a higher probability of fatal injury in a newer vehicle compared with females, all other factors kept constant. These effects lend support to the use of mixed logit models in injury severity research and show age and gender based population heterogeneity.
Several other factors were found to significantly increase the probability of fatal injury for drivers in single-vehicle crashes, most notably: male driver, drunk driving, unsafe speed, older driver (65+) driving an older vehicle, and darkness without streetlights.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>22939394</pmid><doi>10.1016/j.aap.2012.08.011</doi><tpages>9</tpages></addata></record> |
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| source | MEDLINE; Access via ScienceDirect (Elsevier) |
| subjects | Accidents, Traffic - statistics & numerical data Adult Age Age Factors Aged Automobile Driving Biological and medical sciences California - epidemiology Female Gender Heterogeneity Humans Injury severity Injury Severity Score Logistic Models Male Medical sciences Middle Aged Miscellaneous Mixed logit Prevention and actions Public health. Hygiene Public health. Hygiene-occupational medicine Risk Factors Sex Factors Single-vehicle |
| title | Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender |
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