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Objective: To examine associations between work and commute hours with food consumption and test whether neighbourhood type (20-minute neighbourhood (20MN)/non-20MN) moderate associations. Design: Cross-sectional analysis of the Places and Locations for Activity and Nutrition study (ProjectPLAN). Exposures were work hours (not working (0 h), working up to full-time (1–38 h/week), working overtime (> 38 h/week)), and among those employed, combined weekly work and commute hours (continuous). Outcomes were usual consumption of fruit, vegetables, takeaway food, snacks and soft drinks, and number of discretionary food types (takeaway, snacks and soft drinks) consumed weekly. Generalised linear models were fitted to examine associations between each exposure and outcome. The moderating role of neighbourhood type was examined through interaction terms between each exposure and neighbourhood type (20MN/non-20MN). Setting: Melbourne and Adelaide, Australia, 2018–2019. Participants: Adults ≥ 18 years old (n 769). Results: Although all confidence intervals contained the null, overall, patterns suggested non-workers and overtime workers have less healthy food behaviours than up-to-full-time workers. Among those employed, analysis of continuous work and commute hours data suggested longer work and commute hours were positively associated with takeaway consumption (OR = 1·014, 95 % CI 0·999, 1·030, P -value = 0·066). Patterns of better behaviours were observed across most outcomes for those in 20MN than non-20MN. However, differences in associations between work and commute hours with food consumption across neighbourhood type were negligible. Conclusions: Longer work and commute hours may induce poorer food behaviours. There was weak evidence to suggest 20MN moderate associations between work and commute hours with food consumption, although behaviours appeared healthier for those in 20MN. [ABSTRACT FROM AUTHOR]

Objective: To explore differences in proportion of food budget and total food expenditure by dwelling type.Design: A cross-sectional study using data from the Australian Bureau of Statistics 2015-2016 Household Expenditure Survey. Food expenditure was examined on multiple categories: fresh fruits, fresh vegetables, pre-prepared meals, meals in restaurants, hotels and clubs, and fast food and takeaway meals, using two-part models and zero-one inflated beta regression models. Dwelling types were categorised as separate house, semi-detached house, low-rise apartment and high-rise apartment.Setting: Australia, 2015-2016.Participants: Seven thousand three hundred and fifty-eight households from greater capital city areas.Results: Households living in high-rise apartments were estimated to allocate a greater proportion of their food budget to meals in restaurants, hotels and clubs, and to spend more (actual dollars) on that category, compared with other dwelling types. No substantial differences were estimated in the proportion of food budget allocated to the other food categories across dwelling types.Conclusions: The dwelling type households live in may play a role in their food budget. Households living in a high-rise apartment may potentially spend more on meals in restaurants, hotels and clubs than those living in other dwelling types. Given the growth in urban population and the changes in living arrangements, findings point to the critical need for a better understanding of the influence of dwelling types on food expenditure and call for research investigating the relationship between the two. [ABSTRACT FROM AUTHOR]

Abstract Background Using two different measures of park area, at three buffer distances, we sought to investigate the ways in which park area and proximity to parks, are related to the frequency of walking (for all purposes) in Australian adults. Little previous research has been conducted in this area, and results of existing research have been mixed. Methods Residents of 50 urban areas in metropolitan Melbourne, Australia completed a physical activity survey (n = 2305). Respondents reported how often they walked for ≥10 minutes in the previous month. Walking frequency was dichotomised to ‘less than weekly’ (less than 1/week) and ‘at least weekly’ (1/week or more). Using Geographic Information Systems, Euclidean buffers were created around each respondent’s home at three distances: 400metres (m), 800 m and 1200 m. Total area of parkland in each person’s buffer was calculated for the three buffers. Additionally, total area of ‘larger parks’, (park space ≥ park with Australian Rules Football oval (17,862 m2)), was calculated for each set of buffers. Area of park was categorised into tertiles for area of all parks, and area of larger parks (the lowest tertile was used as the reference category). Multilevel logistic regression, with individuals nested within areas, was used to estimate the effect of area of parkland on walking frequency. Results No statistically significant associations were found between walking frequency and park area (total and large parks) within 400 m of respondent’s homes. For total park area within 800 m, the odds of walking at least weekly were lower for those in the mid (OR 0.65, 95% CI 0.46-0.91) and highest (OR 0.65, 95% CI 0.44-0.95) tertile of park area compared to those living in areas with the least amount of park area. Similar results were observed for total park area in the 1200 m buffers. When only larger parks were investigated, again more frequent walking was less likely when respondents had access to a greater amount of park area. Conclusions In this study we found that more park area in residential environments reduced the odds of walking more frequently. Other area characteristics such as street connectivity and destinations may underlie these associations by negatively correlating with park area.

Abstract Background Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale. Method Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the ‘Health and Well-Being’ Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models. Results Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008). Conclusions The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning.

Abstract Background Supermarkets play a major role in influencing the food purchasing behaviours of most households. Snack food exposures within these stores may contribute to higher levels of consumption and ultimately to increasing levels of obesity, particularly within socioeconomically disadvantaged neighbourhoods. We aimed to examine the availability of snack food displays at checkouts, end-of-aisle displays and island displays in major supermarket chains in the least and most socioeconomically disadvantaged neighbourhoods of Melbourne. Methods Within-store audits of 35 Melbourne supermarkets. Supermarkets were sampled from the least and most socioeconomically disadvantaged suburbs within 30 km of the Melbourne CBD. We measured the availability of crisps, chocolate, confectionery, and soft drinks (diet and regular) at the checkouts, in end-of-aisle displays, and in island bin displays. Results Snack food displays were most prominent at checkouts with only five stores not having snack foods at 100% of their checkouts. Snack foods were also present at a number of end-of-aisle displays (at both the front (median 38%) and back (median 33%) of store), and in island bin displays (median number of island displays: 7; median total circumference of island displays: 19.4 metres). Chocolate items were the most common snack food item on display. There was no difference in the availability of these snack food displays by neighbourhood disadvantage. Conclusions As a result of the high availability of snack food displays, exposure to snack foods is almost unavoidable in Melbourne supermarkets, regardless of levels of neighbourhood socioeconomic disadvantage. Results of this study could promote awareness of the prominence of unhealthy food items in chain-brand supermarkets outlets.

Abstract 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.

Abstract 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) – 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 – 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.