title: Associations between individual socioeconomic position, neighbourhood disadvantage and transport mode: baseline results from the HABITAT multilevel study.
abstract: BACKGROUND
  Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP), and usual transport mode.
  
  
  METHODS
  This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomial logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category.
  
  
  RESULTS
  Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR 1.68, 95% CrI 1.41-2.01), members of lower income households (OR 1.71 95% CrI 1.25-2.30) and residents of more disadvantaged neighbourhoods (OR 1.93, 95% CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95% CrI 0.49-0.74) and blue collar workers (OR 0.63, 95% CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95% CrI 1.18-2.11), those not in the labour force (OR 1.94, 95% CrI 1.38-2.72), members of lower income households (OR 2.10, 95% CrI 1.23-3.64) and residents of more disadvantaged neighbourhoods (OR 2.73, 95% CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48).
  
  
  CONCLUSIONS
  The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual-level and neighbourhood-level mechanisms behind choice of transport mode, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.
authors.affiliation: School of Public Health and Social Work and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
authors.forename: Jerome N
authors.identifier: http://orcid.org/0000-0002-5101-4010
authors.initials: JN
authors.lastname: Rachele
authors.affiliation: Gender and Women's Health Unit, Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
authors.forename: Anne M
authors.initials: AM
authors.lastname: Kavanagh
authors.affiliation: McCaughey VicHealth Community Wellbeing Unit, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
authors.forename: Hannah
authors.initials: H
authors.lastname: Badland
authors.affiliation: McCaughey VicHealth Community Wellbeing Unit, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
authors.forename: Billie
authors.initials: B
authors.lastname: Giles-Corti
authors.affiliation: Civil Engineering and Built Environment School, Science and Engineering Faculty, Centre for Accident Research and Road Safety, Health Faculty and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
authors.forename: Simon
authors.initials: S
authors.lastname: Washington
authors.affiliation: School of Public Health and Social Work and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
authors.forename: Gavin
authors.initials: G
authors.lastname: Turrell
mesh_terms: D000328:Adult; D000368:Aged; D001642:Bicycling / Q000706:statistics & numerical data; D004522:Educational Status; D005260:Female; D006801:Humans; D007182:Income; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D018986:Motor Vehicles / Q000706:statistics & numerical data; D055361:Multilevel Analysis; D009790:Occupations / Q000145:classification / Q000191:economics; D011793:Queensland; D012111:Residence Characteristics / Q000145:classification*; D012923:Social Class; D014186:Transportation / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data; D016138:Walking / Q000706:statistics & numerical data
keywords: Health inequalities; MULTILEVEL MODELLING; Neighborhood/place; PHYSICAL ACTIVITY; SOCIAL EPIDEMIOLOGY