We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
To investigate dietary intake, BMI and supermarket access at varying geographic scales and transport modes across areas of socio-economic disadvantage, and to evaluate the implementation of an urban planning policy that provides guidance on spatial access to supermarkets.
Design
Cross-sectional study used generalised estimating equations to investigate associations between supermarket density and proximity, vegetable and fruit intake and BMI at five geographic scales representing distances people travel to purchase food by varying transport modes. A stratified analysis by area-level disadvantage was conducted to detect optimal distances to supermarkets across socio-economic areas. Spatial distribution of supermarket and transport access was analysed using a geographic information system.
Setting
Melbourne, Australia.
Subjects
Adults (n 3128) from twelve local government areas (LGA) across Melbourne.
Results
Supermarket access was protective of BMI for participants in high disadvantaged areas within 800 m (P=0·040) and 1000 m (P=0·032) road network buffers around the household but not for participants in less disadvantaged areas. In urban growth area LGA, only 26 % of dwellings were within 1 km of a supermarket, far less than 80–90 % of dwellings suggested in the local urban planning policy. Low public transport access compounded disadvantage.
Conclusions
Rapid urbanisation is a global health challenge linked to increases in dietary risk factors and BMI. Our findings highlight the importance of identifying the most appropriate geographic scale to inform urban planning policy for optimal health outcomes across socio-economic strata. Urban planning policy implementation in disadvantaged areas within cities has potential for reducing health inequities.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.