Deprivation and food access and balance in Saskatoon, Saskatchewan

Abstract

Introduction We explored food access and balance in Saskatoon, Saskatchewan, Canada in relation to material and social deprivation. Methods We mapped the location of all large supermarkets and fast food retailers in Saskatoon. Supermarket accessibility index scores and food balance scores were compared to material and social deprivation indexes to determine significant associations. Results Our results indicate that the poorest access to supermarkets occurred in areas west of the South Saskatchewan River and also in suburban areas around the perimeter of the city. Areas west of the river are some of the most deprived areas in the city. Saskatoon's mean food balance ratio of 2.3 indicates that access favours fast food. However, we did not find a clear pattern or clear socio-economic gradient for most measures. Conclusion This study highlights the importance of contextual studies of food access. This study also highlighted a number of other issues that should be explored in the Saskatoon context such as individual-level food consumption patterns, mobility, temporal dimensions of food access and economic access as well as interventions that could improve food access in the city.

Health-related outcomes of new grocery store interventions: a systematic review

“…A noteworthy observation was that all of the interventions reviewed had occurred in areas designated as socio-economically disadvantaged or low-income neighbourhoods. People living in these neighbourhoods are at high risk for poor diet due to poor healthy food access, abundance of unhealthy food exposure and poor public transit options ( 43 , 44 ) . Apart from poor healthy food access, many of these neighbourhoods also suffer from low basic public and private services, social exclusion and associated oppressions ( 45 ) .…”

Spatial inequalities of retail food stores may determine availability of healthful food choices in a Brazilian metropolis

“…An inverse relationship was found in some studies carried out in Canada, the United Kingdom, Denmark and Brazil in which economically disadvantaged neighbourhoods tend to have a lower availability of stores selling unhealthy foods (20)(21)(22)(23) . Other studies have been incapable of finding any clear patterns or gradient or any significant associations between neighbourhood characteristics and food environments (24)(25)(26) . Nevertheless, it is important to note that lower availability of stores selling unhealthy foods does not necessarily imply lower exposure to unhealthy food environments.…”

Food environment research in Canada: a rapid review of methodologies and measures deployed between 2010 and 2021

“…The community retail food environment was assessed in 81% of Retail articles, and the consumer retail food environment was analyzed in 27% of Retail articles (Table 3 ). The community retail food environment was frequently assessed within administrative units like census tracts or dissemination areas (38%, n = 27) [ 40 , 41 , 50 , 53 – 55 , 94 – 96 , 108 – 110 , 115 – 129 ], around schools (33%, n = 24) [ 63 – 66 , 68 , 97 – 100 , 102 – 105 , 111 , 112 , 130 – 138 ], around residences (36%, n = 26) [ 58 , 104 , 106 , 113 , 133 , 135 – 137 , 139 – 156 ] and around recreation centres or workplace (3%, n = 2) [ 130 , 140 ]. The consumer retail food environment included in-store (79%, n = 19) [ 49 – 57 , 59 , 62 , 67 , 87 , 90 – 92 , 101 , 114 , 117 ] and restaurant settings (25%, n = 6) [ 53 , 60 , 61 , 107 , 116 , 132 ].…”

“…To identify food stores within a specific area, the most popular data sources among all Retail articles were commercial data (58%) (e.g., Enhanced Points of Interest (EPOI) database from the Desktop Mapping Technologies Inc., Yellow Pages), administrative data from jurisdictions applying to the study setting (39%) and ground-truthing (11%). In articles related to the community retail food environment ( n = 72), analysis of food outlets ‘exposure’ or accessibility were most frequently performed with place-based measures (90%), among which 66% ( n = 43) used fixed spatial units such as areas around schools [ 53 , 54 , 58 , 63 – 66 , 68 , 97 – 100 , 102 – 106 , 111 , 112 , 127 , 130 – 132 , 134 – 141 , 143 , 144 , 146 – 152 , 154 – 156 ] or residences, or area-based anchors (45%, n = 29) such as census tracts [ 40 , 41 , 50 , 55 , 95 , 96 , 106 , 108 , 109 , 115 – 128 , 133 , 139 – 142 , 153 ]. Fewer publications (6%) assessed food outlets exposure through people-based measures, such as individual's Global Positioning System (GPS) trajectory data or travel survey data, which take into account the various food environments people get exposed to when they accomplish their daily routine by tracking and mapping people’s daily mobility and activities [ 41 ].…”

“…Fewer publications (6%) assessed food outlets exposure through people-based measures, such as individual's Global Positioning System (GPS) trajectory data or travel survey data, which take into account the various food environments people get exposed to when they accomplish their daily routine by tracking and mapping people’s daily mobility and activities [ 41 ]. In the majority of articles related to the community retail food environment (72%), buffers were purposely designed by researchers to define the study area, either using straight line (42%, n = 22; i.e., radial buffer) [ 53 , 54 , 64 – 66 , 68 , 97 – 100 , 102 , 104 , 105 , 111 , 112 , 115 , 117 , 130 , 135 – 137 , 150 ] or road network (52%, n = 27) measures [ 58 , 99 , 100 , 103 , 104 , 109 , 116 , 118 , 120 , 121 , 128 , 132 , 134 , 138 – 141 , 143 , 144 , 146 – 149 , 153 – 156 ]. There was no mention on the type of buffers used in 13% of publications ( n = 7) [ 63 , 102 , 114 , 125 , 133 , 151 , 152 ].…”