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Understanding these relationships is essential for addressing residential self-selection bias.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Using 25\u2005years (6 examinations) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (n=11\u2005013 observations) and linked neighbourhood-level data from the 4 CARDIA baseline cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California, USA), we characterised participants\u2019 neighbourhoods as having low, average or high road connectivity and amenities using non-hierarchical cluster analysis. We then used repeated measures multinomial logistic regression with random effects to examine the associations between individual-level sociodemographics and neighbourhood-level characteristics with residential neighbourhood types over the 25-year period, and whether these associations differed by individual-level income.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Being female was positively associated with living in neighbourhoods with low (vs high) road connectivity and activity-related and diet-related amenities among high-income individuals only. At all income levels, a higher percentage of neighbourhood white population and neighbourhood population &lt;18\u2005years were associated with living in neighbourhoods with low (vs high) connectivity and amenities. Individual-level race; age; and educational attainment, neighbourhood socioeconomic status and housing prices did not influence residential location behaviour related to neighbourhood connectivity and amenities at any income level.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Neighbourhood-level factors appeared to play a comparatively greater role in shaping residential location behaviour than individual-level sociodemographics. Our study is an important step in understanding how residential locational behaviour relates to amenities and physical activity opportunities, and may help mitigate residential self-selection bias in built environment studies.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/jech-2016-207249","type":"journal-article","created":{"date-parts":[[2016,9,22]],"date-time":"2016-09-22T22:29:30Z","timestamp":1474583370000},"page":"261-268","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":9,"title":["How do individual-level sociodemographics and neighbourhood-level characteristics influence residential location behaviour in the context of the food and built environment? Findings from 25\u2005years of follow-up in the CARDIA Study"],"prefix":"10.1136","volume":"71","author":[{"given":"Pasquale E","family":"Rummo","sequence":"first","affiliation":[{"name":"Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Carolina Population Center, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David K","family":"Guilkey","sequence":"additional","affiliation":[{"name":"Department of Economics, University of North Carolina at Chapel Hill, Carolina Population Center, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James M","family":"Shikany","sequence":"additional","affiliation":[{"name":"Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jared P","family":"Reis","sequence":"additional","affiliation":[{"name":"Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Penny","family":"Gordon-Larsen","sequence":"additional","affiliation":[{"name":"Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Carolina Population Center, Chapel Hill, North Carolina, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2016,9,22]]},"reference":[{"key":"2025100301003601000_71.3.261.1","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychsport.2009.09.003"},{"key":"2025100301003601000_71.3.261.2","doi-asserted-by":"publisher","DOI":"10.1080\/00420980500185611"},{"key":"2025100301003601000_71.3.261.3","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2009.02.002"},{"key":"2025100301003601000_71.3.261.4","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-011-9360-y"},{"key":"2025100301003601000_71.3.261.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2005.12.005"},{"key":"2025100301003601000_71.3.261.6","doi-asserted-by":"publisher","DOI":"10.1068\/a45490"},{"key":"2025100301003601000_71.3.261.7","doi-asserted-by":"publisher","DOI":"10.1249\/MSS.0b013e318247d286"},{"key":"2025100301003601000_71.3.261.8","doi-asserted-by":"crossref","first-page":"21","DOI":"10.5198\/jtlu.v1i2.65","article-title":"The role of employment subcenters in residential location decisions","volume":"1","author":"Cho","year":"2008","journal-title":"J Transport Land Use"},{"key":"2025100301003601000_71.3.261.9","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-007-9153-5"},{"key":"2025100301003601000_71.3.261.10","doi-asserted-by":"publisher","DOI":"10.3141\/2133-10"},{"key":"2025100301003601000_71.3.261.11","doi-asserted-by":"publisher","DOI":"10.3141\/1902-08"},{"key":"2025100301003601000_71.3.261.12","doi-asserted-by":"publisher","DOI":"10.5198\/jtlu.v7i2.740"},{"key":"2025100301003601000_71.3.261.13","doi-asserted-by":"publisher","DOI":"10.1080\/01944361003646471"},{"key":"2025100301003601000_71.3.261.14","doi-asserted-by":"publisher","DOI":"10.1177\/0042098014527138"},{"key":"2025100301003601000_71.3.261.15","unstructured":"Zillow Neighborhood Boundaries. http:\/\/www.zillow.com\/howto\/api\/neighborhood-boundaries.htm (access Date: 5\/15\/2015)."},{"key":"2025100301003601000_71.3.261.16","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3389\/fpubh.2016.00065","article-title":"Obtaining longitudinal built environment data retrospectively across 25 years in four US cities","volume":"4","author":"Hirsch","year":"2016","journal-title":"Front Public Health"},{"key":"2025100301003601000_71.3.261.17","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-005-7027-2"},{"key":"2025100301003601000_71.3.261.18","doi-asserted-by":"publisher","DOI":"10.1016\/j.healthplace.2010.04.013"},{"key":"2025100301003601000_71.3.261.19","first-page":"391","article-title":"Symptom clustering in subjects with and without diabetes mellitus: a population-based study of 15,000 Australian adults","volume":"98","author":"Hammer","year":"2003","journal-title":"Am J Gastroenterol"},{"key":"2025100301003601000_71.3.261.20","doi-asserted-by":"publisher","DOI":"10.1007\/s11524-006-9094-x"},{"key":"2025100301003601000_71.3.261.21","unstructured":"Chen C , Burgos AC , Mehra S , et al . 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