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Objective: To examine the extent to which characteristics of the neighborhood built environment explain the association between adiposity and educational qualifications in Australian women., Methods: A community sample of 1,819 women (aged 18-66) from the Melbourne SESAW study provided information regarding their body mass index (BMI) and level of education. Objective measures of participants' residential neighborhood built environments were obtained using a Geographic Information System., Results: Compared with women with a high school degree or above, women who did not complete high school had higher average BMI, which was partially explained by lower density of sports facilities and living less proximally to the coastline and to supermarkets. In a multiple mediator model, which explained 16.6% of the educational disparity in BMI, the number of sports facilities and presence of the coastline within 2 km of participants' homes were significant mediators of the observed socioeconomic disparity in BMI., Conclusions: The residential neighborhood environment may help to explain socioeconomic patterning of overweight and obesity in Australian women. These results provide further support for considering the built environment in obesity prevention initiatives, suggesting a potential role in decreasing social inequalities in obesity., (© 2014 The Obesity Society.)

An aggregate index is potentially useful to represent neighbourhood obesogenicity. We created a conceptually-based obesogenicity index and examined its association with body mass index (BMI) among 3786 women (age 18-45y) in socio-economically disadvantaged neighbourhoods in Victoria, Australia. The index included 3 items from each of 3 domains: food resources (supermarkets, green grocers, fast food restaurants), recreational activity resources (gyms, pools, park space), and walkability (4+ leg intersections, neighbourhood walking environment, neighbourhood safety), with a possible range from 0 to 18 reflecting 0-2 for each of the 9 items. Using generalised estimating equations, neighbourhood obesogenicity was not associated with BMI in the overall sample. However, stratified analyses revealed generally positive associations with BMI in urban areas and inverse associations in rural areas (interaction p=0.02). These analyses are a first step towards combining neighbourhood characteristics into an aggregate obesogenicity index that is transparent enough to be adopted elsewhere and to allow examination of the relevance of its specific components in different settings., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The Resilience for Eating and Activity Despite Inequality (READI) cohort was established to address the following two key aims: to investigate the pathways (personal, social and structural) by which socio-economic disadvantage influences lifestyle choices associated with obesity risk (physical inactivity, poor dietary choices) and to explore mechanisms underlying 'resilience' to obesity risk in socio-economically disadvantaged women and children. A total of 4349 women aged 18-46 years and 685 children aged 5-12 years were recruited from 80 socio-economically disadvantaged urban and rural neighbourhoods of Victoria, Australia, and provided baseline (T1: 2007-08) measures of adiposity, physical activity, sedentary and dietary behaviours; socio-economic and demographic factors; and psychological, social and perceived environmental factors that might impact on obesity risk. Audits of the 80 neighbourhoods were undertaken at baseline to provide objective neighbourhood environmental data. Three-year follow-up data (2010-11) have recently been collected from 1912 women and 382 children. Investigators welcome enquiries regarding data access and collaboration.

Increase in the consumption of food and drinks outside the home by adolescents and young people and associations with rising levels of obesity is a significant concern worldwide and it has been suggested that the food environment around schools may be a contributory factor. As few studies have explored this issue in a UK setting, we examined whether different types of food outlets are clustered around public secondary schools in Glasgow, and whether this pattern differed by social disadvantage. We found evidence of clustering of food outlets around schools but a more complex picture in relation to deprivation was observed. Across all schools there were numerous opportunities for pupils to purchase energy dense foods locally and the implications for policy are discussed., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

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.

Issue addressed: This study systematically reviewed Australian literature to determine if an association exists between geospatial exposure to food outlets and diet, health or weight status. Recommendations for future research are provided. Methods: A systematic literature search was conducted in December 2021 using CINAHL Plus, PubMed and Web of Science databases. Data were extracted, as per the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. Study quality was assessed using an eight‐item checklist. A descriptive synthesis of study characteristics and findings was carried out, stratified via study outcomes. Results: Of the 36 included articles, the majority were from Victoria (n = 19), involving adult participants (n = 30) and cross‐sectional in design (n = 27). Overall, associations were mainly null (nonsignificant) for diet (80%), weight status (75%) and health outcomes (90%). Significant findings were mixed with no positive trend with study quality. Conclusions: Six recommendations are suggested to address current knowledge gaps and limitations in the Australian evidence base: (1) Conduct research on different populations; (2) Employ robust study designs that can test the impact of change over time; (3) Improve the accuracy of food outlet data sources; (4) Improve food outlet geospatial exposure measures; (5) Improve measurement of outcome variables; and (6) Incorporate theoretical models into study design and data analysis. So what?: Improving the quality and consistency of research will be critical to informing locally relevant policy. Despite the present limitations in the evidence base, it is reasonable to assume that decisions to purchase and consume food are driven by availability and access. Thus, policy and planning aimed at improving the overall "healthiness" of the community food environment by increasing access to healthy food outlets is warranted to ensure that healthy options are easier choice for all. [ABSTRACT FROM AUTHOR]

Issue addressed: Locating fast‐food outlets near schools is a potential public health risk to schoolchildren, given the easy access and repeated exposure to energy‐dense, nutrient‐poor foods they provide. Fast‐food outlet availability near schools has not been previously investigated in Perth, Western Australia. This study aimed to quantify fast‐food outlet availability near Perth schools and determine whether differences in area‐level disadvantage and school type exist. Methods: Fast‐food outlet locations were sourced from Perth Local Governments in 2018/2019. All Perth Primary (n = 454), Secondary (n = 107) and K‐12 (n = 94) schools were assigned an area‐level disadvantage decile ranking based on the Australian Bureau of Statistics Socio‐Economic Index for Areas (SEIFA). Regression models assessed whether fast‐food outlet availability within 400 m, 800 m and 1 km of schools differed by school type (ie, Primary/Secondary/K‐12) or SEIFA. Results: Secondary schools were significantly more likely than Primary and K‐12 schools to have a higher presence and density of fast‐food outlets and the "Top 4" fast‐food outlet chains (McDonalds, Hungry Jacks, KFC and Red Rooster) nearby. Schools located in low socio‐economic status (SES) areas had a significantly higher density of fast‐food outlets within 400 m, and "Top 4" fast‐food outlet chains within 400 m and 1 km, than schools located in high SES area. Conclusions: Perth schools are surrounded by fast‐food outlets with densities significantly higher around secondary schools and schools located in lower SES areas. So what?: Policies and regulations aimed at reducing fast‐food outlets near schools is an essential strategy to improve dietary intakes and reduce obesity in schoolchildren. [ABSTRACT FROM AUTHOR]

Background: To identify longitudinal individual, social and environmental predictors of adiposity (BMI z-score), and of resilience to unhealthy weight gain, in healthy weight children and adolescents. Methods: Two hundred healthy weight children aged 5-12 years at baseline and their parents living in socio-economically disadvantaged neighborhoods were surveyed at baseline and three years later. Children's height and weight were objectively measured, parents completed a detailed questionnaire that examined the home, social and neighborhood environments, and objective measures of the neighborhood environment were assessed using geographic information system data. Children classified as healthy weight at baseline who had small or medium increases in their BMI z-score between baseline and three year follow up (those in the bottom and middle tertiles) were categorized as 'resilient to unhealthy weight gain'. Where applicable, fully adjusted multivariable regression models were employed to determine baseline intrapersonal, social and environmental predictors of child BMI z-scores at follow-up, and resilience to unhealthy weight gain at follow-up. Results: Maternal efficacy for preventing their child from engaging in sedentary behaviors (B = -0.03, 95 % CI: -0.06, 0.00) was associated with lower child BMI z-score at follow up. Rules to limit sedentary behaviors (OR = 1.14, 95 % CI: 1.03, 1.25) was a predictor of being resilient to unhealthy weight gain. Conclusion: The findings suggest that strategies to support parents to limit their children's sedentary behavior may be important in preventing unhealthy weight gain in socioeconomically disadvantaged communities. [ABSTRACT FROM AUTHOR]