To explore store-specific grocery shopping patterns and assess associations with the objective and perceived retail food environment (RFE).

This cross-sectional study used principal component analysis and hierarchical cluster analysis to identify grocery shopping patterns and logistic regression models to assess their associations with the RFE, while adjusting for household characteristics.

The Montpellier Metropolitan Area, France.

To be eligible for inclusion, participants had to be 18 years of age or older and reside in the Montpellier Metropolitan Area. Analyses were carried out on 415 households.

Households of cluster ‘Supermarket’ (49 % of households) primarily shopped at supermarkets and were less likely to live near a convenience store. Households of cluster ‘Diversified’ (18 %) shopped mostly at organic stores, at markets, at specialised stores, and from producers and were more likely to have a market in their activity space. Households of cluster ‘Discount’ (12 %) primarily shopped at discounters and were less likely to perceive a producer in their activity space. Households of cluster ‘Convenience’ (12 %) mostly shopped online or in convenience stores. Finally, households of cluster ‘Specialized’ (9 %) had high expenditures in greengrocers and in other specialised food stores and were more likely to live near a specialised food store.

This study highlighted the importance of considering both perceived and objective RFE indicators, as well as assessments around the home and in activity space. Understanding how people buy food and interact with their RFE is crucial for policymakers seeking to improve urban food policies.

To examine the potential links between activity spaces, the food retail environment and food shopping behaviours for the population of young, urban adults.

Participants took part in the Canada Food Study, which collected information on demographics, food behaviour, diet and health, as well as an additional smartphone study that included a seven-day period of logging GPS (global positioning system) location and food purchases. Using a time-weighted, continuous representation of participant activity spaces generated from GPS trajectory data, the locations of food purchases and a geocoded food retail data set, negative binomial regression models were used to explore what types of food retailers participants were exposed to and where food purchases were made.

Toronto, Montreal, Vancouver, Edmonton and Halifax, Canada.

Young adults aged 16–30 years (n 496). These participants were a subset of the larger Canada Food Study.

Demographics, household food shopper status and city of residence were significantly associated with different levels of exposure to various types of food retailers. Food shopping behaviours were also statistically significantly associated with demographics, the activity space-based food environment, self-reported health and city of residence.

The study confirms that food behaviours are related to activity space-based food environment measures, which provide a more comprehensive accounting of food retail exposure than home-based measures. In addition, exposure to food retail and food purchasing behaviours of an understudied population are described.

To explore associations between dietary quality and access to different types of food outlets around both home and school in primary school-aged children.

Cross-sectional observational study.

Hampshire, UK.

Children (n 1173) in the Southampton Women’s Survey underwent dietary assessment at age 6 years by FFQ and a standardised diet quality score was calculated. An activity space around each child’s home and school was created using ArcGIS. Cross-sectional observational food outlet data were overlaid to derive four food environment measures: counts of supermarkets, healthy specialty stores (e.g. greengrocers), fast-food outlets and total number of outlets, and a relative measure representing healthy outlets (supermarkets and specialty stores) as a proportion of total retail and fast-food outlets.

In univariate multilevel linear regression analyses, better diet score was associated with exposure to greater number of healthy specialty stores (β=0·025 sd/store: 95 % CI 0·007, 0·044) and greater exposure to healthy outlets relative to all outlets in children’s activity spaces (β=0·068 sd/10 % increase in healthy outlets as a proportion of total outlets, 95 % CI 0·018, 0·117). After adjustment for mothers’ educational qualification and level of home neighbourhood deprivation, the relationship between diet and healthy specialty stores remained robust (P=0·002) while the relationship with the relative measure weakened (P=0·095). Greater exposure to supermarkets and fast-food outlets was associated with better diet only in the adjusted models (P=0·017 and P=0·014, respectively).

The results strengthen the argument for local authorities to increase the number of healthy food outlets to which young children are exposed.