2021
DOI: 10.1016/j.jth.2021.101122
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Residential location, commute distance, and body size: Cross-sectional observational study of state and territory capital cities in Australia

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Cited by 6 publications
(5 citation statements)
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“…Similar findings have been reported in other Australian studies [55]. We also found residents of neighbourhoods more distant from the CBD had greater BMI (in seven of eight cities [Darwin is the exception]) and a larger waist circumference (in five cities, with Hobart, Darwin and Canberra the exceptions) than residents of neighbourhoods closer to the CBD, which also concurs with previous Australian research [44]. Building on the foregoing, our multivariable modelling showed that when associations between neighbourhood disadvantage and body size were adjusted for residential distance to the CBD, the magnitude of the neighbourhood differences were attenuated in Sydney, Melbourne, Brisbane, Adelaide, and Perth: between 28.5% and 4.0% for BMI, and between 26.8% and 4.7% for waist circumference.…”
Section: Plos Onesupporting
confidence: 92%
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“…Similar findings have been reported in other Australian studies [55]. We also found residents of neighbourhoods more distant from the CBD had greater BMI (in seven of eight cities [Darwin is the exception]) and a larger waist circumference (in five cities, with Hobart, Darwin and Canberra the exceptions) than residents of neighbourhoods closer to the CBD, which also concurs with previous Australian research [44]. Building on the foregoing, our multivariable modelling showed that when associations between neighbourhood disadvantage and body size were adjusted for residential distance to the CBD, the magnitude of the neighbourhood differences were attenuated in Sydney, Melbourne, Brisbane, Adelaide, and Perth: between 28.5% and 4.0% for BMI, and between 26.8% and 4.7% for waist circumference.…”
Section: Plos Onesupporting
confidence: 92%
“…To support our secondary aim of assessing generalisability of findings from one city to other cities, and due to findings from previous studies using the NHS data which indicated between-city variation in the relationships between environmental indicators and body size [44,45] analyses in this study were stratified by city. A multi-level modelling approach was used with the unit of analysis at the level of the individual, adjusting for covariates and accounting for clustering of individuals within SA1's.…”
Section: Analytic Dataset and Analytic Approachmentioning
confidence: 99%
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“…In a longitudinal study of Swedish workers, and controlling for neighborhood SES and other factors, commuting distance had a dose response relationship with physical inactivity (Raza et al, 2021). These health behaviours can affect weight and studies of in-vehicle time, commute distance, and commute time show associations with BMI or obesity (Carroll et al, 2021;Dunton et al, 2009;Frank et al, 2004;Hoehner et al, 2012;Künn-Nelen, 2016;McCormack and Virk, 2014;Sha et al, 2019;Sugiyama et al, 2020).…”
mentioning
confidence: 99%