Fast food restaurant locations : could they be \u27supersizing\u27 local communities?

This review examines the current state of knowledge related to the location of fast food restaurants. Previous studies have revealed some communities are more exposed to fast food restaurants. However, the influence of increased exposure to fast food on dietary behaviours remains unresolved. This is identified as an area of priority for future research.<br /

Australian rock coasts : review and prospects

Studies of Australian rock coasts (except carbonate reefs) are reviewed and considered in view of recent process and morphological studies. The unique nature of the Australian coast, its geographical distribution and relative stability mean that it is a productive environment in which to research fundamental questions concerning rock coasts. Future research directions are identified, specifically in the areas of processes, morphology and modelling. <br /

Employment status, residential and workplace food environments: associations with women\u27s eating behaviours

There remains a lack of consistent evidence linking food environments with eating behaviours. Studies to date have largely ignored the way different individuals interact with their local food environment and have primarily focussed on exposures within the residential neighbourhood without consideration of exposures around the workplace, for example. In this study we firstly examine whether associations between the residential food environment and eating behaviours differ by employment status and, secondly, whether food environments near employed women\u27s workplaces are more strongly associated with dietary behaviours than food environments near home. Employment status did not modify the associations between residential food environments and eating behaviours, however results showed that having access to healthy foods near the workplace was associated with healthier food consumption. Policies focused on supportive environments should consider commercial areas as well as residential neighbourhoods

Who is eating where? Findings from the SESAW study

Objective: Foods prepared outside of the home have been linked to less-than-ideal nutrient profiles for health. We examine whether the locations where meals are prepared and consumed are associated with socio-economic predictors among women.Design: A cross-sectional study using self-reported data. We examined multiple locations where meals are prepared and consumed: (i) at home; (ii) fast food eaten at home; (iii) fast food eaten at the restaurant; (iv) total fast food; (v) non-fast-food restaurant meals eaten at home; (vi) non-fast-food restaurant meals eaten at the restaurant; and (vii) all non-fast-food restaurant meals. Multilevel logistic regression was used to determine whether frequent consumption of meals from these sources varied by level of education, occupation, household income and area-level disadvantage.Setting: Metropolitan Melbourne, Australia.Subjects: A total of 1328 women from forty-five neighbourhoods randomly sampled for the SocioEconomic Status and Activity in Women study.Results: Those with higher educational qualifications or who were not in the workforce (compared with those in professional employment) were more likely to report frequent consumption of meals prepared and consumed at home. High individual and area-level socio-economic characteristics were associated with a lower likelihood of frequent consumption of fast food and a higher likelihood of frequent consumption of meals from non-fast-food sources. The strength and significance of relationships varied by place of consumption.Conclusions: The source of meal preparation and consumption varied by socioeconomic predictors. This has implications for policy makers who need to continue to campaign to make healthy alternatives available in out-of-home food sources.<br /

Statistical approaches used to assess the equity of access to food outlets: a systematic review

Abstract: Background 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&ndash;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 numberof 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.<br /

Reduced food access due to a lack of money, inability to lift and lack of access to a car for food shopping : a multilevel study in Melbourne, Victoria

Objective: To describe associations between demographic and individual and arealevel socio-economic variables and restricted household food access due to lack of money, inability to lift groceries and lack of access to a car to do food shopping.Design: Multilevel study of three measures of restricted food access, i.e. running out of money to buy food, inability to lift groceries and lack of access to a car for food shopping. Multilevel logistic regression was conducted to examine the risk of each of these outcomes according to demographic and socio-economic variables.Setting: Random selection of households from fifty small areas in Melbourne, Australia, in 2003.Subjects: The main food shoppers in each household (n 2564).Results: A lack of money was significantly more likely among the young and in households with single adults. Difficultly lifting was more likely among the elderly and those born overseas. The youngest and highest age groups both reported reduced car access, as did those born overseas and single-adult households. All three factors were most likely among those with a lower individual or household socio-economic position. Increased levels of area disadvantage were independently associated with difficultly lifting and reduced car access.Conclusions: In Melbourne, households with lower individual socio-economic position and area disadvantage have restricted access to food because of a lack of money and/or having physical limitations due difficulty lifting or lack of access to a car for food shopping. Further research is required to explore the relationship between physical restrictions and food access.<br /

Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary

Features of the built environment are increasingly being recognised as potentially important determinants of obesity. This has come about, in part, because of advances in methodological tools such as Geographic Information Systems (GIS). GIS has made the procurement of data related to the built environment easier and given researchers the flexibility to create a new generation of environmental exposure measures such as the travel time to the nearest supermarket or calculations of the amount of neighbourhood greenspace. Given the rapid advances in the availability of GIS data and the relative ease of use of GIS software, a glossary on the use of GIS to assess the built environment is timely. As a case study, we draw on aspects the food and physical activity environments as they might apply to obesity, to define key GIS terms related to data collection, concepts, and the measurement of environmental features

Fast food purchasing and access to fast food restaurants: a multilevel analysis of VicLANES

Background : While previous research on fast food access and purchasing has not found evidence of an association, these studies have had methodological problems including aggregation error, lack of specificity between the exposures and outcomes, and lack of adjustment for potential confounding. In this paper we attempt to address these methodological problems using data from the Victorian Lifestyle and Neighbourhood Environments Study (VicLANES) &ndash; a cross-sectional multilevel study conducted within metropolitan Melbourne, Australia in 2003.Methods : The VicLANES data used in this analysis included 2547 participants from 49 census collector districts in metropolitan Melbourne, Australia. The outcome of interest was the total frequency of fast food purchased for consumption at home within the previous month (never, monthly and weekly) from five major fast food chains (Red Rooster, McDonalds, Kentucky Fried Chicken, Hungry Jacks and Pizza Hut). Three measures of fast food access were created: density and variety, defined as the number of fast food restaurants and the number of different fast food chains within 3 kilometres of road network distance respectively, and proximity defined as the road network distance to the closest fast food restaurant. Multilevel multinomial models were used to estimate the associations between fast food restaurant access and purchasing with never purchased as the reference category. Models were adjusted for confounders including determinants of demand (attitudes and tastes that influence food purchasing decisions) as well as individual and area socio-economic characteristics.Results : Purchasing fast food on a monthly basis was related to the variety of fast food restaurants (odds ratio 1.13; 95% confidence interval 1.02 &ndash; 1.25) after adjusting for individual and area characteristics. Density and proximity were not found to be significant predictors of fast food purchasing after adjustment for individual socio-economic predictors.Conclusion : Although we found an independent association between fast food purchasing and access to a wider variety of fast food restaurant, density and proximity were not significant predictors. The methods used in our study are an advance on previous analyses.<br /