Demographic factors, workplace factors and active transportation use in the USA: a secondary analysis of 2009 NHTS data
Background While active transportation has health, economic and environmental benefits, participation within the USA is low. The purpose of this study is to examine relationships of demographic and workplace factors with health-enhancing active transportation and commuting. Methods Participants in t...
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| Veröffentlicht in: | Journal of epidemiology and community health (1979) 2017-05, Vol.71 (5), p.480-486 |
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| creator | Quinn, Tyler D Jakicic, John M Fertman, Carl I Gibbs, Bethany Barone |
| description | Background While active transportation has health, economic and environmental benefits, participation within the USA is low. The purpose of this study is to examine relationships of demographic and workplace factors with health-enhancing active transportation and commuting. Methods Participants in the 2009 National Household Travel Survey reported demographics, workplace factors (time/distance to work, flextime availability, option to work from home and work start time) and active transportation (for any purpose) or commuting (to and from work, workers only) as walking or biking (≥10 min bouts only). Multiple logistic regression examined cross-sectional relationships between demographics and workplace factors with active transportation and commuting. Results Among 152 573 participants, active transportation was reported by 1.11% by biking and 11.74% by walking. Among 111 808 working participants, active commuting was reported by 0.80% by biking and 2.76% by walking. Increased odds (p |
| doi_str_mv | 10.1136/jech-2016-207820 |
| format | Article |
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The purpose of this study is to examine relationships of demographic and workplace factors with health-enhancing active transportation and commuting. Methods Participants in the 2009 National Household Travel Survey reported demographics, workplace factors (time/distance to work, flextime availability, option to work from home and work start time) and active transportation (for any purpose) or commuting (to and from work, workers only) as walking or biking (≥10 min bouts only). Multiple logistic regression examined cross-sectional relationships between demographics and workplace factors with active transportation and commuting. Results Among 152 573 participants, active transportation was reported by 1.11% by biking and 11.74% by walking. Among 111 808 working participants, active commuting was reported by 0.80% by biking and 2.76% by walking. Increased odds (p<0.05) of active commuting and transportation were associated with younger age, lower income, urban dwelling, and the highest and lowest education categories. Males had greater odds of commuting and transporting by bike but decreased odds of walk transporting. Inconsistent patterns were observed by race, but whites had greater odds of any biking (p<0.05). Odds of active commuting were higher with a flexible schedule (p<0.001), the option to work from home (p<0.05), shorter time and distance to work (both p<0.001), and work arrival time between 11:00 and 15:59 (walking only, p=0.001). Conclusions Active transportation differed across demographic and workplace factors. These relationships could inform infrastructure policy decisions and workplace wellness programming targeting increased active transportation.</description><identifier>ISSN: 0143-005X</identifier><identifier>EISSN: 1470-2738</identifier><identifier>DOI: 10.1136/jech-2016-207820</identifier><identifier>PMID: 27986862</identifier><language>eng</language><publisher>England: BMJ Publishing Group Ltd</publisher><subject>Adult ; Bicycling - statistics & numerical data ; Choice Behavior ; Commuting ; Cross-Sectional Studies ; Demography ; Design ; Diaries ; Exercise ; Female ; Health Behavior ; Health Promotion ; Households ; Humans ; Institutional repositories ; Logistic Models ; Male ; Middle Aged ; Mortality ; Occupational health ; Participation ; Public health ; Research report ; Secondary analysis ; Transportation ; Transportation - methods ; Travel ; Travel - statistics & numerical data ; United States ; Walking ; Walking - statistics & numerical data ; Workers ; Workplace - statistics & numerical data ; Young Adult</subject><ispartof>Journal of epidemiology and community health (1979), 2017-05, Vol.71 (5), p.480-486</ispartof><rights>2017 BMJ Publishing Group</rights><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.</rights><rights>Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c448t-ed169dee811b2c9724c2c66699593d1dedd820d4e917db90adf4722fbc681b233</citedby><cites>FETCH-LOGICAL-c448t-ed169dee811b2c9724c2c66699593d1dedd820d4e917db90adf4722fbc681b233</cites><orcidid>0000-0002-0732-6148 ; 0000-0001-6910-0956</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26164463$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26164463$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>315,781,785,804,27928,27929,58021,58254</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27986862$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Quinn, Tyler D</creatorcontrib><creatorcontrib>Jakicic, John M</creatorcontrib><creatorcontrib>Fertman, Carl I</creatorcontrib><creatorcontrib>Gibbs, Bethany Barone</creatorcontrib><title>Demographic factors, workplace factors and active transportation use in the USA: a secondary analysis of 2009 NHTS data</title><title>Journal of epidemiology and community health (1979)</title><addtitle>J Epidemiol Community Health</addtitle><description>Background While active transportation has health, economic and environmental benefits, participation within the USA is low. The purpose of this study is to examine relationships of demographic and workplace factors with health-enhancing active transportation and commuting. Methods Participants in the 2009 National Household Travel Survey reported demographics, workplace factors (time/distance to work, flextime availability, option to work from home and work start time) and active transportation (for any purpose) or commuting (to and from work, workers only) as walking or biking (≥10 min bouts only). Multiple logistic regression examined cross-sectional relationships between demographics and workplace factors with active transportation and commuting. Results Among 152 573 participants, active transportation was reported by 1.11% by biking and 11.74% by walking. Among 111 808 working participants, active commuting was reported by 0.80% by biking and 2.76% by walking. Increased odds (p<0.05) of active commuting and transportation were associated with younger age, lower income, urban dwelling, and the highest and lowest education categories. Males had greater odds of commuting and transporting by bike but decreased odds of walk transporting. Inconsistent patterns were observed by race, but whites had greater odds of any biking (p<0.05). Odds of active commuting were higher with a flexible schedule (p<0.001), the option to work from home (p<0.05), shorter time and distance to work (both p<0.001), and work arrival time between 11:00 and 15:59 (walking only, p=0.001). Conclusions Active transportation differed across demographic and workplace factors. These relationships could inform infrastructure policy decisions and workplace wellness programming targeting increased active transportation.</description><subject>Adult</subject><subject>Bicycling - statistics & numerical data</subject><subject>Choice Behavior</subject><subject>Commuting</subject><subject>Cross-Sectional Studies</subject><subject>Demography</subject><subject>Design</subject><subject>Diaries</subject><subject>Exercise</subject><subject>Female</subject><subject>Health Behavior</subject><subject>Health Promotion</subject><subject>Households</subject><subject>Humans</subject><subject>Institutional repositories</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Occupational health</subject><subject>Participation</subject><subject>Public health</subject><subject>Research report</subject><subject>Secondary analysis</subject><subject>Transportation</subject><subject>Transportation - methods</subject><subject>Travel</subject><subject>Travel - statistics & numerical data</subject><subject>United States</subject><subject>Walking</subject><subject>Walking - statistics & numerical data</subject><subject>Workers</subject><subject>Workplace - statistics & numerical data</subject><subject>Young Adult</subject><issn>0143-005X</issn><issn>1470-2738</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkU1PGzEQhq0K1ATaey8gS71wYFvb6_iDGwqfUtQeAKk3y7Fnmw2b9WLvNuLf4xAoEicu9sh-3pFmHoS-UfKD0lL8XIJbFIxQkQ-pGPmExpRLUjBZqh00JpSXBSGTPyO0l9KS5FIy_RmNmNRKKMHGaH0Gq_A32m5RO1xZ14eYjvE6xPuusQ5en7BtPc5l_Q9wH22buhB729ehxUMCXLe4XwC-uzk9wRYncKH1Nj7mlG0eU51wqDAjRONfV7c32NvefkG7lW0SfH2599Hdxfnt9KqY_b68np7OCse56gvwVGgPoCidM6cl4445IYTWE1166sH7PLbnoKn0c02sr7hkrJo7oXKiLPfR0bZvF8PDAKk3qzo5aBrbQhiSoUpTJSWfiA-gEyZ03rPM6Pd36DIMMQ-bDKOaCy3Uc0OypVwMKUWoTBfrVd6LocRs_JmNP7PxZ7b-cuTwpfEwX4H_H3gVloGDLbBM2cvbv6CCc1GWT0OvnxU</recordid><startdate>20170501</startdate><enddate>20170501</enddate><creator>Quinn, Tyler D</creator><creator>Jakicic, John M</creator><creator>Fertman, Carl I</creator><creator>Gibbs, Bethany Barone</creator><general>BMJ Publishing Group Ltd</general><general>BMJ Publishing Group LTD</general><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>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>7T2</scope><scope>7U2</scope><scope>C1K</scope><orcidid>https://orcid.org/0000-0002-0732-6148</orcidid><orcidid>https://orcid.org/0000-0001-6910-0956</orcidid></search><sort><creationdate>20170501</creationdate><title>Demographic factors, workplace factors and active transportation use in the USA: a secondary analysis of 2009 NHTS data</title><author>Quinn, Tyler D ; Jakicic, John M ; Fertman, Carl I ; Gibbs, Bethany Barone</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c448t-ed169dee811b2c9724c2c66699593d1dedd820d4e917db90adf4722fbc681b233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Bicycling - statistics & numerical data</topic><topic>Choice Behavior</topic><topic>Commuting</topic><topic>Cross-Sectional Studies</topic><topic>Demography</topic><topic>Design</topic><topic>Diaries</topic><topic>Exercise</topic><topic>Female</topic><topic>Health Behavior</topic><topic>Health Promotion</topic><topic>Households</topic><topic>Humans</topic><topic>Institutional repositories</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Occupational health</topic><topic>Participation</topic><topic>Public health</topic><topic>Research report</topic><topic>Secondary analysis</topic><topic>Transportation</topic><topic>Transportation - methods</topic><topic>Travel</topic><topic>Travel - statistics & numerical data</topic><topic>United States</topic><topic>Walking</topic><topic>Walking - statistics & numerical data</topic><topic>Workers</topic><topic>Workplace - statistics & numerical data</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Quinn, Tyler D</creatorcontrib><creatorcontrib>Jakicic, John M</creatorcontrib><creatorcontrib>Fertman, Carl I</creatorcontrib><creatorcontrib>Gibbs, Bethany Barone</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</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>Journal of epidemiology and community health (1979)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Quinn, Tyler D</au><au>Jakicic, John M</au><au>Fertman, Carl I</au><au>Gibbs, Bethany Barone</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Demographic factors, workplace factors and active transportation use in the USA: a secondary analysis of 2009 NHTS data</atitle><jtitle>Journal of epidemiology and community health (1979)</jtitle><addtitle>J Epidemiol Community Health</addtitle><date>2017-05-01</date><risdate>2017</risdate><volume>71</volume><issue>5</issue><spage>480</spage><epage>486</epage><pages>480-486</pages><issn>0143-005X</issn><eissn>1470-2738</eissn><abstract>Background While active transportation has health, economic and environmental benefits, participation within the USA is low. The purpose of this study is to examine relationships of demographic and workplace factors with health-enhancing active transportation and commuting. Methods Participants in the 2009 National Household Travel Survey reported demographics, workplace factors (time/distance to work, flextime availability, option to work from home and work start time) and active transportation (for any purpose) or commuting (to and from work, workers only) as walking or biking (≥10 min bouts only). Multiple logistic regression examined cross-sectional relationships between demographics and workplace factors with active transportation and commuting. Results Among 152 573 participants, active transportation was reported by 1.11% by biking and 11.74% by walking. Among 111 808 working participants, active commuting was reported by 0.80% by biking and 2.76% by walking. Increased odds (p<0.05) of active commuting and transportation were associated with younger age, lower income, urban dwelling, and the highest and lowest education categories. Males had greater odds of commuting and transporting by bike but decreased odds of walk transporting. Inconsistent patterns were observed by race, but whites had greater odds of any biking (p<0.05). Odds of active commuting were higher with a flexible schedule (p<0.001), the option to work from home (p<0.05), shorter time and distance to work (both p<0.001), and work arrival time between 11:00 and 15:59 (walking only, p=0.001). Conclusions Active transportation differed across demographic and workplace factors. These relationships could inform infrastructure policy decisions and workplace wellness programming targeting increased active transportation.</abstract><cop>England</cop><pub>BMJ Publishing Group Ltd</pub><pmid>27986862</pmid><doi>10.1136/jech-2016-207820</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-0732-6148</orcidid><orcidid>https://orcid.org/0000-0001-6910-0956</orcidid></addata></record> |
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| subjects | Adult Bicycling - statistics & numerical data Choice Behavior Commuting Cross-Sectional Studies Demography Design Diaries Exercise Female Health Behavior Health Promotion Households Humans Institutional repositories Logistic Models Male Middle Aged Mortality Occupational health Participation Public health Research report Secondary analysis Transportation Transportation - methods Travel Travel - statistics & numerical data United States Walking Walking - statistics & numerical data Workers Workplace - statistics & numerical data Young Adult |
| title | Demographic factors, workplace factors and active transportation use in the USA: a secondary analysis of 2009 NHTS data |
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