Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach

Abstract

BackgroundObesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density.MethodsThis research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas.ResultsFor the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps.ConclusionsThis research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

Food swamps by area socioeconomic deprivation in New Zealand: a national study

“…A wide range of studies investigated the relationships between community retail food environments and area socioeconomic deprivation (Apparicio et al 2007;Gordon et al 2011;Pearce et al 2007aPearce et al , b, 2008aShort et al 2007;Walker et al 2010). Geographic areas with disproportionate access to outlets with an overabundance of high-energy nutrient-poor foods are described as 'Food Swamps' (Luan et al 2015;Osorio et al 2013;Rose et al 2009). …”

Assessing trends and seasonal changes in elephant poaching risk at the small area level using spatio-temporal Bayesian modeling

“…., T. The purely spatial variation is represented by an intercept α (average elephant poaching for the study region), u i (unstructured random effects) and s i (spatially structured random effects). These terms accommodate any overdispersion that may arise when modeling count data at the areal level (Luan et al 2015). Regional temporal variation of elephant poaching for the study region is captured by ƴ.…”

“…neighborhood structure, information from adjacent blocks or experts) to estimate posterior distributions of unknown parameters (e.g. local differential trends in elephant poaching) (Luan et al 2015). The prior data reflect the knowledge available on model parameters before observing the current data (Stigler 1986, Schoot et al 2014.…”

“…An improper uniform prior U (−∞, +∞) was defined for the intercept α (Luan et al 2015). A normal distribution prior with mean 0 and variance σ s 2 was specified for u i .…”

Understanding healthy food environments in public health practice

“…Food swamps are neighbourhoods that have adequate access to healthy food choices, but also feature an overabundance of opportunities to access less healthy food options (Luan et al, 2015;Minaker et al, 2016).…”