{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T03:40:53Z","timestamp":1759722053792,"version":"build-2065373602"},"reference-count":39,"publisher":"BMJ","issue":"9","funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"crossref","award":["ID 497236, 339718, 1047453"],"award-info":[{"award-number":["ID 497236, 339718, 1047453"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Epidemiol Community Health"],"accepted":{"date-parts":[[2025,3,11]]},"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Longitudinal evidence regarding the associations between residential density, walking for transport (WfT) and body mass index (BMI) is limited, and how these relationships vary across different neighbourhood socioeconomic contexts is not yet known. Therefore, we examined longitudinal associations between residential density and BMI: the mediating role of WfT and the moderating effects of neighbourhood disadvantage.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Data from the HABITAT (<jats:underline>H<\/jats:underline>ow <jats:underline>A<\/jats:underline>reas in <jats:underline>B<\/jats:underline>risbane <jats:underline>I<\/jats:underline>nfluence Heal<jats:underline>T<\/jats:underline>h and <jats:underline>A<\/jats:underline>c<jats:underline>T<\/jats:underline>ivity) multilevel longitudinal (2007\u20132016) study of 11\u2009035 middle-aged adult residents of 200 neighbourhoods in Brisbane, Australia, were used. Residential density was objectively assessed within a 1\u2009km network buffer around residents\u2019 homes, and BMI was calculated from self-reported height and weight. Participants self-reported their previous week\u2019s minutes of WfT. Generalised structural equation modelling was used to estimate the mediating effect of WfT in explaining residential density\u2013BMI associations across the quintiles of neighbourhood disadvantage, adjusting for time-varying and time-invariant confounders, including distance to Brisbane Central Business District (CBD) and residential self-selection.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Residents living in high-density neighbourhoods were found to engage in more WfT and maintain a lower BMI. WfT mediated approximately 6.44% of the density\u2013BMI relationships. These longitudinal relationships remained consistent in moderately disadvantaged neighbourhoods but differed in areas with other levels of disadvantage and when accounting for CBD distance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Residentially dense neighbourhoods facilitate transport-related walking, potentially reducing the risk of weight-related chronic conditions. However, these effects vary across different neighbourhood socioeconomic contexts. Urban planning and policy efforts should focus on context-specific measures to leverage the anticipated benefits of residential density.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/jech-2024-223095","type":"journal-article","created":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T01:53:25Z","timestamp":1742954005000},"page":"704-711","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Longitudinal associations between residential density and body mass index: the mediating role of walking for transport and the moderating effect of neighbourhood disadvantage"],"prefix":"10.1136","volume":"79","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7064-1178","authenticated-orcid":false,"given":"Samjhana","family":"Shrestha","sequence":"first","affiliation":[{"name":"Health Research Institute, University of Canberra Faculty of Health, Canberra, Australian Capital Territory, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3576-8744","authenticated-orcid":false,"given":"Gavin","family":"Turrell","sequence":"additional","affiliation":[{"name":"Health Research Institute, University of Canberra Faculty of Health, Canberra, Australian Capital Territory, Australia"},{"name":"Healthy Liveable Cities Group, Centre for Urban Research, RMIT University, Melbourne, Victoria, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9767-2860","authenticated-orcid":false,"given":"Suzanne J","family":"Carroll","sequence":"additional","affiliation":[{"name":"Health Research Institute, University of Canberra Faculty of Health, Canberra, Australian Capital Territory, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2025,3,25]]},"reference":[{"unstructured":"Australian Bureau of Statistics . 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