Neighborhood Socioeconomic Deprivation and Minority Composition Are Associated with Better Potential Spatial Access to the Ground-Truthed Food Environment in a Large Rural Area

Abstract

Little is known about spatial inequalities and potential access to the food environment in rural areas. In this study, we assessed the food environment in a 6-county rural region of Texas (11,567 km2) through ground-truthed methods that included direct observation and on-site Global Positioning System technology to examine the relationship between neighborhood inequalities (e.g., socioeconomic deprivation and minority composition) and network distance from all 101 rural neighborhoods to the nearest food store (FS). Neighborhood deprivation was determined from socioeconomic characteristics using 2000 census block group (CBG) data. Network distances were calculated from the population-weighted center of each CBG to the nearest supermarket, grocery, convenience, and discount store. Multiple regression models examined associations among deprivation, minority composition, population density, and network distance to the nearest FS. The median distance to the nearest supermarket was 14.9 km one way (range 0.12 to 54.0 km). The distance decreased with increasing deprivation, minority composition, and population density. The worst deprived neighborhoods with the greatest minority composition had better potential spatial access to the nearest FS. For >20% of all rural residents, their neighborhoods were at least 17.7 km from the nearest supermarket or full-line grocery or 7.6 km from the nearest convenience store. This makes food shopping a challenge, especially in rural areas that lack public transportation and where many have no vehicular access. Knowledge of potential access to the food environment is essential for combining environmental approaches and health interventions so that families, especially those in rural areas, can make healthier food choices.

Validation of presence of supermarkets and fast-food outlets in Copenhagen: case study comparison of multiple sources of secondary data

“…Relatively little is published on the validity and reliability of these sources (1) . In a recent review by Kelly and colleagues (2) , methods used to validate the location of food outlets obtained from secondary data range from list cross-referencing (3)(4)(5)(6) to direct observation (7)(8)(9)(10)(11)(12)(13)(14) . Correspondence between sources was reported as percentage match or agreement (6,7,9,10,13,15) , sensitivity (11)(12)(13) or positive predictive value (PPV) (12,13,16) .…”

“…In a recent review by Kelly and colleagues (2) , methods used to validate the location of food outlets obtained from secondary data range from list cross-referencing (3)(4)(5)(6) to direct observation (7)(8)(9)(10)(11)(12)(13)(14) . Correspondence between sources was reported as percentage match or agreement (6,7,9,10,13,15) , sensitivity (11)(12)(13) or positive predictive value (PPV) (12,13,16) . Validation studies reporting correspondence statistics have generally been performed in North America (3,4,6,(9)(10)(11)(12)14,15,17) or the UK (5,7,13,16) .…”

Service District Optimization: Usage of Facility Location Methods and Geographic Information Systems to Analyze and Optimize Urban Food Retail Distribution

“…The exact same approach except for an omission of recent immigrants was used by Larsen and Gilliland (2008). Sharkey and Horel (2008) neglect recent immigrant and lone-parent family figures but include household crowding, public assistance, vehicle availability and telephone service. Unfortunately, there is little reasoning about why certain measures are included.…”

Measuring the Food Environment: From Theory to Planning Practice

“…The concept of food access often reflects a geographical perspective of the food environment and includes measures such as proximity (i.e., distance to the nearest specified type of food outlet) (Apparicio, Cloutier, & Shearmur, 2007;Larsen & Gilliland, 2008;Sharkey & Horel, 2008;Zenk, Schulz, Israel et al, 2005), density (e.g., proportion or ratio of food stores per area, buffer zone, or population; concentration of fast food outlets as measured by locations per roadway mile) (Inagami, Cohen, Brown & Asch, 2009;Moore & DiezRoux, 2006;Moore, Diez-Roux, Nettleton & Jacobs, 2008;Spence, Cutumisu, Edwards, Raine, & Smoyer-Tomic, 2009) and variety (e.g., number of food stores or food service places within a specified buffer zone) (Andreyeva, Blumenthal, Schwartz, Long & Brownell, 2008;Apparicio et al, 2007;Morland & Evenson, 2009). Literature reviews examining the relationship between food access and diet and/or health outcomes have shown generally positive results, with some finding stronger relationships (Holsten, 2009;Larson, Story, & Nelson, 2009;Papas et al, 2007;Walker, Keane, & Burke, 2010) than others (Black & Macinko, 2008;White, 2007).…”