Comparison of spatial approaches to assess the effect of residing in a 20-minute neighbourhood on body mass index
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- ISIDORE Id: 10670/1.0598af...
- hal: hal-03973116
- doi: 10.1016/j.sste.2022.100546
- PUBMED: 36460452
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.sste.2022.100546
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info:eu-repo/semantics/altIdentifier/pmid/36460452
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Mots-clés
urban planning health-environment association spatial analysis spatial autocorrelation Built environmentSujets proches
Addresses Papers, Collected (Anthologies) Orations Collected papers (Anthologies) Discourses Addresses Lecturing Speaking Discourses Pattern Model Commerce--Accounting Finance--Accounting Commercial accounting Business enterprises--Accounting Financial accounting Accountancy BMI (Body mass index)Citer ce document
Guannan Yang et al., « Comparison of spatial approaches to assess the effect of residing in a 20-minute neighbourhood on body mass index », HAL SHS (Sciences de l’Homme et de la Société), ID : 10.1016/j.sste.2022.100546
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Résumé
Beliefs that neighbourhood environments influence body mass index (BMI) assume people residing proximally have similar outcomes. However, spatial relationships are rarely examined. We considered spatial autocorrelation when estimating associations between neighbourhood environments and BMI in two Australian cities. Using cross-sectional data from 1329 participants (Melbourne = 637, Adelaide = 692), spatial autocorrelation in BMI was examined for different spatial weights definitions. Spatial and ordinary least squares regression were compared to assess how accounting for spatial autocorrelation influenced model findings. Geocoded household addresses were used to generate matrices based on distances between addresses. We found low positive spatial autocorrelation in BMI; magnitudes differed by matrix choice, highlighting the need for careful consideration of appropriate spatial weighting. Results indicated statistical evidence of spatial autocorrelation in Adelaide but not Melbourne. Model findings were comparable, with no residual spatial autocorrelation after adjustment for confounders. Future neighbourhoods and BMI research should examine spatial autocorrelation, accounting for this where necessary.
