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dc.contributor.authorLamb, KE
dc.contributor.authorThornton, LE
dc.contributor.authorCerin, E
dc.contributor.authorBall, K
dc.date.accessioned2020-12-10T00:46:07Z
dc.date.available2020-12-10T00:46:07Z
dc.date.issued2015-01-01
dc.identifierpii: publichealth-02-03-358
dc.identifier.citationLamb, K. E., Thornton, L. E., Cerin, E. & Ball, K. (2015). Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review. AIMS PUBLIC HEALTH, 2 (3), pp.358-401. https://doi.org/10.3934/publichealth.2015.3.358.
dc.identifier.issn2327-8994
dc.identifier.urihttp://hdl.handle.net/11343/253567
dc.description.abstractBackground: Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Methods: Searches were conducted for articles published from 2000-2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Results: Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. Conclusions: With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results.
dc.languageEnglish
dc.publisherAMER INST MATHEMATICAL SCIENCES-AIMS
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleStatistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review
dc.typeJournal Article
dc.identifier.doi10.3934/publichealth.2015.3.358
melbourne.affiliation.departmentMelbourne School of Population and Global Health
melbourne.source.titleAIMS Public Health
melbourne.source.volume2
melbourne.source.issue3
melbourne.source.pages358-401
dc.rights.licenseCC BY
melbourne.elementsid1368010
melbourne.contributor.authorLamb, Karen
dc.identifier.eissn2327-8994
melbourne.accessrightsOpen Access


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