Characterizing the food retail environment: impact of count, type, and geospatial error in 2 secondary data sources

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies.

Designing and Evaluating a Hierarchical Framework for Matching Food Outlets across Multi-sourced Geospatial Datasets: a Case Study of San Diego County

Research on retail food environment (RFE) relies on data availability and accuracy. However, the discrepancies in RFE datasets may lead to imprecision when measuring association with health outcomes. In this research, we present a two-tier hierarchical point of interest (POI) matching framework to compare and triangulate food outlets across multiple geospatial data sources. Two matching parameters were used including the geodesic distance between businesses and the similarity of business names according to Levenshtein distance (LD) and Double Metaphone (DM). Sensitivity analysis was conducted to determine thresholds of matching parameters. Our Tier 1 matching used more restricted parameters to generate high confidence-matched POIs, whereas in Tier 2 we opted for relaxed matching parameters and applied a weighted multi-attribute model on the previously unmatched records. Our case study in San Diego County, California used government, commercial, and crowdsourced data and returned 20.2% matched records from Tier 1 and 18.6% matched from Tier 2. Our manual validation shows a 100% matching rate for Tier 1 and up to 30.6% for Tier 2. Matched and unmatched records from Tier 1 were further analyzed for spatial patterns and categorical differences. Our hierarchical POI matching framework generated highly confident food POIs by conflating datasets and identified some food POIs that are unique to specific data sources. Triangulating RFE data can reduce uncertain and invalid POI listings when representing food environment using multiple data sources. Studies investigating associations between food environment and health outcomes may benefit from improved quality of RFE.

Estimating the effect of latent time-varying count exposures using multiple lists

A major challenge in longitudinal built-environment health studies is the accuracy of commercial business databases that are used to characterize dynamic food environments. Different databases often provide conflicting exposure measures on the same subject due to different source credibilities. As on-site verification is not feasible for historical data, we suggest combining multiple databases to correct the bias in health effect estimates due to measurement error in any 1 datasource. We propose a joint model for the time-varying health outcomes, observed count exposures, and latent true count exposures. Our model estimates the time-specific quality of sources and incorporates time dependence of true count exposure by Poisson integer-valued first-order autoregressive process. We take a Bayesian nonparametric approach to flexibly account for location-specific exposures. By resolving the discordance between different databases, our method reduces the bias in the longitudinal health effect of the true exposures. Our method is demonstrated with childhood obesity data in California public schools with respect to convenience store exposures in school neighborhoods from 2001 to 2008.

Neighborhood Racial Segregation Predict the Spatial Distribution of Supermarkets and Grocery Stores Better than Socioeconomic Factors in Cleveland, Ohio: a Bayesian Spatial Approach

INTRODUCTION

The food environment influences the availability and affordability of food options for consumers in a given neighborhood. However, disparities in access to healthy food options exist, affecting Black and low-income communities disproportionately. This study investigated whether racial segregation predicted the spatial distribution of supermarkets and grocery stores better than socioeconomic factors or vice versa in Cleveland, Ohio.

METHOD

The outcome measure was the count of supermarket and grocery stores in each census tract in Cleveland. They were combined with US census bureau data as covariates. We fitted four Bayesian spatial models. The first model was a baseline model with no covariates. The second model accounted for racial segregation alone. The third model looked at only socioeconomic factors, and the final model combined both racial and socioeconomic factors.

RESULTS

Overall model performance was better in the model that considered only racial segregation as a predictor of supermarkets and grocery stores (DIC = 476.29). There was 13% decrease in the number of stores for a census tract with a higher majority of Black people compared to areas with a lower number of Black people. Model 3 that considered only socioeconomic factors was less predictive of the retail outlets (DIC = 484.80).

CONCLUSIONS

These findings lead to the conclusion that structural racism evidenced in policies like residential segregation has a significant influence on the spatial distribution of food retail in the city of Cleveland.

National trends and disparities in retail food environments in the USA between 1990 and 2014

OBJECTIVE

To describe national disparities in retail food environments by neighbourhood composition (race/ethnicity and socio-economic status) across time and space.

DESIGN

We examined built food environments (retail outlets) between 1990 and 2014 for census tracts in the contiguous USA (n 71 547). We measured retail food environment as counts of all food stores, all unhealthy food sources (including fast food, convenience stores, bakeries and ice cream) and healthy food stores (including supermarkets, fruit and vegetable markets) from National Establishment Time Series business data. Changes in food environment were mapped to display spatial patterns. Multi-level Poisson models, clustered by tract, estimated time trends in counts of food stores with a land area offset and independent variables population density, racial composition (categorised as predominantly one race/ethnicity (>60 %) or mixed), and inflation-adjusted income tertile.

SETTING

The contiguous USA between 1990 and 2014.

PARTICIPANTS

All census tracts (n 71 547).

RESULTS

All food stores and unhealthy food sources increased, while the subcategory healthy food remained relatively stable. In models adjusting for population density, predominantly non-Hispanic Black, Hispanic, Asian and mixed tracts had significantly more destinations of all food categories than predominantly non-Hispanic White tracts. This disparity increased over time, predominantly driven by larger increases in unhealthy food sources for tracts which were not predominantly non-Hispanic White. Income and food store access were inversely related, although disparities narrowed over time.

CONCLUSIONS

Our findings illustrate a national food landscape with both persistent and shifting spatial patterns in the availability of establishments across neighbourhoods with different racial/ethnic and socio-economic compositions.

Participatory mapping to address neighborhood level data deficiencies for food security assessment in Southeastern Virginia, USA

Background

Food is not equitably available. Deficiencies and generalizations limit national datasets, food security assessments, and interventions. Additional neighborhood level studies are needed to develop a scalable and transferable process to complement national and internationally comparative data sets with timely, granular, nuanced data. Participatory geographic information systems (PGIS) offer a means to address these issues by digitizing local knowledge.

Methods

The objectives of this study were two-fold: (i) identify granular locations missing from food source and risk datasets and (ii) examine the relation between the spatial, socio-economic, and agency contributors to food security. Twenty-nine subject matter experts from three cities in Southeastern Virginia with backgrounds in food distribution, nutrition management, human services, and associated research engaged in a participatory mapping process.

Results

Results show that publicly available and other national datasets are not inclusive of non-traditional food sources or updated frequently enough to reflect changes associated with closures, expansion, or new programs. Almost 6 percent of food sources were missing from publicly available and national datasets. Food pantries, community gardens and fridges, farmers markets, child and adult care programs, and meals served in community centers and homeless shelters were not well represented. Over 24 km2 of participant identified need was outside United States Department of Agriculture low income, low access areas. Economic, physical, and social barriers to food security were interconnected with transportation limitations. Recommendations address an international call from development agencies, countries, and world regions for intervention methods that include systemic and generational issues with poverty, incorporate non-traditional spaces into food distribution systems, incentivize or regulate healthy food options in stores, improve educational opportunities, increase data sharing.

Conclusions

Leveraging city and regional agency as appropriate to capitalize upon synergistic activities was seen as critical to achieve these goals, particularly for non-traditional partnership building. To address neighborhood scale food security needs in Southeastern Virginia, data collection and assessment should address both environment and utilization issues from consumer and producer perspectives including availability, proximity, accessibility, awareness, affordability, cooking capacity, and preference. The PGIS process utilized to facilitate information sharing about neighborhood level contributors to food insecurity and translate those contributors to intervention strategies through discussion with local subject matter experts and contextualization within larger scale food systems dynamics is transferable.

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

OBJECTIVE

To examine the association between economic residential segregation and food environment.

DESIGN

Ecological: Food stores categorised according to the NOVA classification were geocoded, and absolute availability was calculated for each neighbourhood. Segregation was measured using local Gi* statistic, a measure of the sd between the economic composition of a neighbourhood (the proportion of heads of households in neighbourhoods earn monthly income of 0 to 3 minimum wages) and larger metropolitan area, weighted by the economic composition of surrounding neighbourhoods. Segregation was categorised as high (most segregated), medium (integrated) and low (less segregated or integrated). A proportional odds models were used to model the association between segregation and food environment.

SETTING

Belo Horizonte, Brazil.

PARTICIPANTS

Food stores.

RESULTS

After adjustment for covariates, neighbourhoods characterised by high economic segregation had fewer food stores overall compared with neighbourhoods characterised by low segregation (OR = 0·56; 95 % CI (0·45, 0·69)). In addition, high segregated neighbourhoods were 49 % (OR = 0·51; 95 % CI (0·42, 0·61)) and 45 % (OR = 0·55; 95 % CI (0·45, 0·67)) less likely to have a high number of food stores that predominantly marketed ultra-processed foods and mixed food stores, respectively, as compared with their counterparts.

CONCLUSIONS

Economic segregation is associated with differences in the distribution of food stores. Both low and high segregation territories should be prioritised by public policies to ensure healthy and adequate nutrition as a right for all communities. The former must continue to be protected from access to unhealthy commercial food outlets, while the latter must be the locus of actions that limit the availability of unhealthy commercial food store.

Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation

To overcome the challenge of obtaining accurate data on community food retail, we developed an innovative tool to automatically capture food retail data from Google Earth (GE). The proposed method is relevant to non-commercial use or scholarly purposes. We aimed to test the validity of web sources data for the assessment of community food retail environment by comparison to ground-truth observations (gold standard). A secondary aim was to test whether validity differs by type of food outlet and socioeconomic status (SES). The study area included a sample of 300 census tracts stratified by SES in two of the largest cities in Brazil, Rio de Janeiro and Belo Horizonte. The GE web service was used to develop a tool for automatic acquisition of food retail data through the generation of a regular grid of points. To test its validity, this data was compared with the ground-truth data. Compared to the 856 outlets identified in 285 census tracts by the ground-truth method, the GE interface identified 731 outlets. In both cities, the GE interface scored moderate to excellent compared to the ground-truth data across all of the validity measures: sensitivity, specificity, positive predictive value, negative predictive value and accuracy (ranging from 66.3 to 100%). The validity did not differ by SES strata. Supermarkets, convenience stores and restaurants yielded better results than other store types. To our knowledge, this research is the first to investigate using GE as a tool to capture community food retail data. Our results suggest that the GE interface could be used to measure the community food environment. Validity was satisfactory for different SES areas and types of outlets.

Google-truthing to assess hot spots of food retail change: A repeat cross-sectional Street View of food environments in the Bronx, New York

Google Street View (GSV) images can be used to "ground-truth" current and historical food retail data from approximately 2007 - when GSV was launched in a few US cities - to the present, facilitating analyses of food environments over time. A review of GSV images of all food retailers listed in a government database of licensed establishments in the Bronx, New York enabled records to be verified, businesses classified, and retail change quantified. The data revealed several trends likely to affect food access and health: increasing overall numbers of food retailers; the growth of dollar stores; and numerous openings, closings, and ownership changes across all food retail segments. Hot spot analysis identified statistically significant clusters of new dollar stores and bodegas, purveyors of less healthy processed foods, in lower-income neighborhoods in the South Bronx that face elevated rates of diet-related diseases. This article demonstrates the benefits and limitations of using GSV to conduct "virtual" food environment research.

Cross-Country Comparison of School Neighborhood Food Environments in Houston, Texas and Guadalajara, Mexico

Studies in the U.S. and Mexico have observed the clustering of food resources around schools, which may promote the use of these resources. Our study characterized and compared school neighborhood food environments in Guadalajara, Jalisco, and Houston, Texas, and examined socioeconomic disparities in food resource availability across school neighborhoods. We used the Goods and Services Inventory to document the frequency and type of resources within each school neighborhood. School neighborhoods in Guadalajara had significantly more food resources than those in Houston. We found that convenience stores and table service restaurants were the most prevalent food resources in school neighborhoods in both cities. Guadalajara school neighborhoods had a higher prevalence of supermarkets and grocery stores than Houston. Low-income school neighborhoods in Guadalajara with poorly educated residents had significantly more food carts than high-income neighborhoods with more educated residents. In Houston, we found significantly more fast food restaurants and convenience stores in school neighborhoods with more educated residents than school neighborhoods with less educated residents. The influence of food resources within school neighborhoods on the dietary habits of schoolchildren should be further explored in both the U.S. and Mexico. The characterization of school neighborhood food environments can inform policymakers, city planners, and school officials who seek to implement policies to create healthier food environments.

Improvement in food environments may help prevent childhood obesity: Evidence from a 9-year cohort study

BACKGROUND

Effects of food environments (FEs) on childhood obesity are mixed.

OBJECTIVES

To examine the association of residential FEs with childhood obesity and variation of the association across gender and urbanicity.

METHODS

We used the US Early Childhood Longitudinal Study-Kindergarten Cohort data, with 9440 kindergarteners followed up from 1998 to 2007. The Dun and Bradstreet commercial datasets in 1998 and 2007 were used to construct 12 FE measures of children, ie, changes in the food outlet mix and density of supermarkets, convenience stores, full-service restaurants, fast-food restaurants, retail bakery, dairy-product stores, health/dietetic food stores, confectionery stores, fruit/vegetable markets, meat/fish markets, and beverage stores. Two-level mixed-effect and cluster robust logistic regression models were fitted to examine associations.

RESULTS

Decreased exposures to full-service restaurants, retail bakeries, fruit/vegetable markets, and beverage stores were generally obesogenic, while decreased exposure to dairy-product stores was generally obesoprotective; the magnitude and statistical significance of these associations varied by gender and urbanicity of residence. Higher obesity risk was associated with increased exposure to full-service restaurants among girls, and with decreased exposures to fruit/vegetable markets in urban children, to beverage stores in suburban children, and to health/dietetic food stores in rural children. Mixed findings existed between genders on the associations of fruit/vegetable markets with child weight status.

CONCLUSION

In the United States, exposure to different FEs seemed to lead to different childhood obesity risks during 1998 to 2007; the association varied across gender and urbanicity. This study has important implications for future urban design and community-based interventions in fighting the obesity epidemic.

Characterizing Rural Food Access in Remote Areas

Residents of rural areas may have limited access to healthy foods, leading to higher incidence of diet related health issues. Smaller grocers in rural areas experience challenges in maintaining fresh produce and other healthy foods available for customers. This study assessed the rural food environment in northeast Lower Michigan in order to inform healthy food financing projects such as the Michigan Good Food Fund. The area's retail food businesses were categorized using secondary licensing, business, and nutrition program databases. Twenty of these stores were visited in person to verify the validity of the categories created, and to assess the availability of healthy foods in their aisles. In-depth interviews with key informants were carried out with store owners, economic development personnel, and other food system stakeholders having knowledge about food access, in order to learn more about the specific challenges that the area faces. Out-shopping, seasonality, and economic challenges were found to affect healthy food availability. Mid-sized independent stores were generally found to have a larger selection of healthy foods, but smaller rural groceries also have potential to provide fresh produce and increase food access. Potential healthy food financing projects are described and areas in need of further research are identified.

Evaluating Community Measures of Healthy Food Access

Several community level measures of healthy food access exist, but evaluation efforts have been limited leaving uncertainty about how to prioritize communities for intervention. This study aimed to assess several existing measures to inform statewide public health planning efforts in New Jersey, USA. We assessed agreement between community measures of healthy food access and then evaluated the predictive validity of each measure by describing its association with complete fruit and vegetable cash-value voucher redemption (proportion redeemed ≥70, ≥80, ≥90%) among 30,078 low-income households participating in the New Jersey Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) during 2013-2014. The United States Department of Agriculture's (USDA) food desert measure agreed with the Centers for Disease Control and Prevention's (CDC) no healthier food retailers (NHFR) measure for 76.5% of New Jersey census tracts, but the Kappa statistic was only 0.10. For urban households, the NHFR measure was negatively associated with complete redemption after adjusting for demographic factors and Supplemental Nutrition Assistance Program participation (≥70% odds ratio (OR) 0.68, 95% confidence interval (CI) 0.61-0.75; ≥80% OR 0.67, 95% CI 0.62-0.73; ≥90% OR 0.72, 95% CI 0.66-0.77). For rural households, a negative association was observed for the USDA's low-income/low-vehicle access measure (≥70% OR 0.48, 95% CI 0.26-0.90). The CDC's NHFR measure is more appropriate for prioritizing urban areas while the USDA's low-income/low-vehicle access measure may be better for rural areas.

Neighborhood Environments and Physical Activity: A Longitudinal Study of Adolescents in a Natural Experiment

INTRODUCTION

Experimental and quasi-experimental evidence on the relationship between adolescents' physical activity and their physical activity environments is scarce. This study provides natural experimental evidence using within-person longitudinal variation in physical activity environments resulting from the compulsory re-assignment of military families to new installations, termed permanent changes of station.

METHODS

Adolescents in Army families (N=749) reported usual weekly minutes of moderate and vigorous physical activity in 2013-2015. Objective measures of the physical activity environment, including the number of fitness and recreation facilities within 2 miles, were constructed for adolescents' neighborhoods using GIS methods. In 2017, individual-level fixed-effects models with and without a comparison group estimated the relationship between usual weekly minutes of physical activity and physical activity environments among permanent changes of station movers using within-person variation.

RESULTS

Increases in opportunities for physical activity were significantly and positively associated with increases in total (p<0.05) and vigorous physical activity (p<0.05) among adolescents who experienced permanent changes of station moves. The relationships were statistically significant for permanent changes of station movers living off-installation (p<0.05) and hence subject to greater variation in physical activity environments and those with more time to adjust to their new environments (p<0.05). Significant findings persisted when broader measures of physical activity environments were utilized.

CONCLUSIONS

The decline in physical activity and alarming obesity levels during adolescence suggest that this age may represent an important opportunity to address the obesity epidemic. This study provides evidence that increasing opportunities for physical activity may be an important pathway to improving their levels of physical activity and, consequently, obesity.

Neighborhood characteristics, food deserts, rurality, and type 2 diabetes in youth: Findings from a case-control study

Little is known about the influence of neighborhood characteristics on risk of type 2 diabetes (T2D) among youth. We used data from the SEARCH for Diabetes in Youth Case-Control Study to evaluate the association of neighborhood characteristics, including food desert status of the census tract, with T2D in youth. We found a larger proportion of T2D cases in tracts with lower population density, larger minority population, and lower levels of education, household income, housing value, and proportion of the population in a managerial position. However, most associations of T2D with neighborhood socioeconomic characteristics were attributable to differences in individual characteristics. Notably, in multivariate logistic regression models, T2D was associated with living in the least densely populated study areas, and this finding requires further exploration.

Relationships between Vacant Homes and Food Swamps: A Longitudinal Study of an Urban Food Environment

Research indicates that living in neighborhoods with high concentrations of boarded-up vacant homes is associated with premature mortality due to cancer and diabetes, but the mechanism for this relationship is unclear. Boarded-up housing may indirectly impact residents’ health by affecting their food environment. We evaluated the association between changes in vacancy rates and changes in the density of unhealthy food outlets as a proportion of all food outlets, termed the food swamp index, in Baltimore, MD (USA) from 2001 to 2012, using neighborhood fixed-effects linear regression models. Over the study period, the average food swamp index increased from 93.5 to 95.3 percentage points across all neighborhoods. Among non-African American neighborhoods, increases in the vacancy rate were associated with statistically significant decreases in the food swamp index (b = −0.38; 90% CI, −0.64 to −0.12; p-value: 0.015), after accounting for changes in neighborhood SES, racial diversity, and population size. A positive association was found among low-SES neighborhoods (b = 0.15; 90% CI, 0.037 to 0.27; p-value: 0.031). Vacant homes may influence the composition of food outlets in urban neighborhoods. Future research should further elucidate the mechanisms by which more distal, contextual factors, such as boarded-up vacant homes, may affect food choices and diet-related health outcomes.

Using Social Media to Identify Sources of Healthy Food in Urban Neighborhoods

An established body of research has used secondary data sources (such as proprietary business databases) to demonstrate the importance of the neighborhood food environment for multiple health outcomes. However, documenting food availability using secondary sources in low-income urban neighborhoods can be particularly challenging since small businesses play a crucial role in food availability. These small businesses are typically underrepresented in national databases, which rely on secondary sources to develop data for marketing purposes. Using social media and other crowdsourced data to account for these smaller businesses holds promise, but the quality of these data remains unknown. This paper compares the quality of full-line grocery store information from Yelp, a crowdsourced content service, to a "ground truth" data set (Detroit Food Map) and a commercially-available dataset (Reference USA) for the greater Detroit area. Results suggest that Yelp is more accurate than Reference USA in identifying healthy food stores in urban areas. Researchers investigating the relationship between the nutrition environment and health may consider Yelp as a reliable and valid source for identifying sources of healthy food in urban environments.

Stretching Food and Being Creative: Caregiver Responses to Child Food Insecurity

OBJECTIVE

To examine the strategies and behaviors caregivers use to manage the household food supply when their children experience food insecurity as measured by the US Department of Agriculture's Household Food Security Survey Module.

DESIGN

Cross-sectional survey with open-ended questions collected in person.

SETTING

Urban and nonurban areas, South Carolina, US.

PARTICIPANTS

Caregivers who reported food insecurity among their children (n = 746).

PHENOMENON OF INTEREST

Strategies and behaviors used to manage the household food supply.

ANALYSIS

Emergent and thematic qualitative coding of open-ended responses.

RESULTS

The top 3 strategies and behaviors to change meals were (1) changes in foods purchased or obtained for the household, (2) monetary and shopping strategies, and (3) adaptations in home preparation. The most frequently mentioned foods that were decreased were protein foods (eg, meat, eggs, beans), fruits, and vegetables. The most frequently mentioned foods that were increased were grains and starches (eg, noodles), protein foods (eg, beans, hot dogs), and mixed foods (eg, sandwiches).

CONCLUSIONS AND IMPLICATIONS

Caregivers use a wide variety of strategies and behaviors to manage the household food supply when their children are food insecure. Future work should examine how these strategies might affect dietary quality and well-being of food-insecure children.

Quantifying the foodscape: A systematic review and meta-analysis of the validity of commercially available business data

This paper reviews studies of the validity of commercially available business (CAB) data on food establishments ("the foodscape"), offering a meta-analysis of characteristics associated with CAB quality and a case study evaluating the performance of commonly-used validity indicators describing the foodscape. Existing validation studies report a broad range in CAB data quality, although most studies conclude that CAB quality is "moderate" to "substantial". We conclude that current studies may underestimate the quality of CAB data. We recommend that future validation studies use density-adjusted and exposure measures to offer a more meaningful characterization of the relationship of data error with spatial exposure.

GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity

Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity.Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minute-level epochs. GPS records were linked to 250 m resolution satellite-based vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations from linearity using splines.Results: Among 360 adult women (mean age of 55.3 ± 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged.Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability.Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. Cancer Epidemiol Biomarkers Prev; 26(4); 525-32. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Longitudinal Associations between Change in Neighborhood Social Disorder and Change in Food Swamps in an Urban Setting

Few studies have examined how neighborhood contextual features may influence the food outlet mix. We evaluated the relationship between changes in neighborhood crime and changes in the food environment, namely the relative density of unhealthy (or intermediate) food outlets out of total food outlets, or food swamp score, in Baltimore City from 2000 to 2012, using neighborhood fixed-effects linear regression models. Comparing neighborhoods to themselves over time, each unit increase in crime rate was associated with an increase in the food swamp score (b = 0.13; 95% CI, -0.00017 to 0.25). The association with food swamp score was in the same direction for violent crime and in the inverse direction for arrests related to juvenile crimes (proxy of reduced crime), but did not reach statistical significance when examined separately. Unfavorable conditions, such as crime, may deter a critical consumer base, diminishing the capacity of a community to attract businesses that are perceived to be neighborhood enhancing. Addressing these more distal drivers may be important for policies and programs to improve these food environments.

A step-by-step approach to improve data quality when using commercial business lists to characterize retail food environments

BACKGROUND

Food environment characterization in health studies often requires data on the location of food stores and restaurants. While commercial business lists are commonly used as data sources for such studies, current literature provides little guidance on how to use validation study results to make decisions on which commercial business list to use and how to maximize the accuracy of those lists. Using data from a retrospective cohort study [Weight And Veterans' Environments Study (WAVES)], we (a) explain how validity and bias information from existing validation studies (count accuracy, classification accuracy, locational accuracy, as well as potential bias by neighborhood racial/ethnic composition, economic characteristics, and urbanicity) were used to determine which commercial business listing to purchase for retail food outlet data and (b) describe the methods used to maximize the quality of the data and results of this approach.

METHODS

We developed data improvement methods based on existing validation studies. These methods included purchasing records from commercial business lists (InfoUSA and Dun and Bradstreet) based on store/restaurant names as well as standard industrial classification (SIC) codes, reclassifying records by store type, improving geographic accuracy of records, and deduplicating records. We examined the impact of these procedures on food outlet counts in US census tracts.

RESULTS

After cleaning and deduplicating, our strategy resulted in a 17.5% reduction in the count of food stores that were valid from those purchased from InfoUSA and 5.6% reduction in valid counts of restaurants purchased from Dun and Bradstreet. Locational accuracy was improved for 7.5% of records by applying street addresses of subsequent years to records with post-office (PO) box addresses. In total, up to 83% of US census tracts annually experienced a change (either positive or negative) in the count of retail food outlets between the initial purchase and the final dataset.

DISCUSSION

Our study provides a step-by-step approach to purchase and process business list data obtained from commercial vendors. The approach can be followed by studies of any size, including those with datasets too large to process each record by hand and will promote consistency in characterization of the retail food environment across studies.

Do GIS-derived measures of fast food retailers convey perceived fast food opportunities? Implications for food environment assessment

PURPOSE

Geographic information systems (GISs) have been used to define fast food availability, with higher availability perhaps promoting poorer quality diets. Alternative measures involve perceptions; however, few studies have examined associations between GIS-derived and perceived measures of the food environment.

METHODS

Telephone surveys of 705 participants within an eight-county region in South Carolina were analyzed using logistic regression to examine relationships between geographic presence of and distance to various types of food retailers and perceived fast food availability.

RESULTS

The mean distance to the nearest fast food restaurant was 6.1 miles, with 16% of participants having a fast food restaurant within 1 mile of home. The geographic presence of and distance to all food retailer types were significantly associated with perceived availability of fast food in unadjusted models. After adjustment, only the presence of a fast food restaurant or pharmacy was significantly associated with greater odds of higher perceived availability of fast food. Greater odds of lower perceived availability of fast food were observed with the presence of a dollar store and increasing distance to the nearest supermarket or pharmacy.

CONCLUSIONS

Measures of fast food availability, whether objective or perceived, may not be interchangeable. Researchers should carefully decide on the appropriate measurement tool-GIS-derived or perceived-in food environment studies.

The context of context: Examining the associations between healthy and unhealthy measures of neighborhood food, physical activity, and social environments

Multilevel health research often focuses on a singular dimension of the neighborhood environment in relation to individual-level health behaviors (e.g., diet, physical activity) and outcomes (e.g., obesity). This study examined associations between healthy and unhealthy neighborhood features across food, physical activity, and social environments. We used neighborhood-level (i.e., census block group) access (0/1) measures of the 1) food (grocery store, convenience store, fast food restaurant), 2) physical activity (fitness/recreation facility, park), and 3) social (crime, renter occupancy) environments to capture both healthy and unhealthy neighborhood features for a sample of neighborhoods (n=126) in East Baton Rouge Parish, Louisiana, United States. We employed a) bivariate correlations, or spatial regression where necessary, to identify significant associations between neighborhood access measures; and b) two-step cluster analysis to identify neighborhood typologies based upon neighborhood access measures. Results demonstrated multiple significant associations between healthy and unhealthy access measures across the three neighborhood environments. Cluster analysis further confirmed that neighborhoods are not completely healthy or unhealthy, but rather can be characterized by neighborhood features that are both health-promoting and health-constraining. This study elucidates a 'context of context' whereby no singular aspect of a neighborhood completely explains health in individuals. Rather, in order to effectively model the association between neighborhood and individual-level health, it may be necessary to account for the inter-related nature of neighborhood features.

Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources

The role of the neighbourhood environment in influencing health behaviours continues to be an important topic in public health research and policy. Foot-based street audits, virtual street audits and secondary data sources are widespread data collection methods used to objectively measure the built environment in environment-health association studies. We compared these three methods using data collected in a nationally representative epidemiological study in 17 British towns to inform future development of research tools. There was good agreement between foot-based and virtual audit tools. Foot based audits were superior for fine detail features. Secondary data sources measured very different aspects of the local environment that could be used to derive a range of environmental measures if validated properly. Future built environment research should design studies a priori using multiple approaches and varied data sources in order to best capture features that operate on different health behaviours at varying spatial scales.

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This study compares multiple data collection methods for measuring built environment features.

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Virtual street audits are reliable for more objective built environment measures.

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Street-based audits are superior for collecting fine detail environmental features.

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Routine secondary data sources need less resources but must be properly validated.

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Appropriate methods for health studies vary depending on the research question and resources.

"Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward.

Moving from policy to implementation: a methodology and lessons learned to determine eligibility for healthy food financing projects

Supplemental Digital Content is Available in the Text.

This article describes a process to implement an eligibility analysis for healthy food financing programs and shares lessons learned from administering the Pennsylvania, New York, and New Orleans healthy food financing programs over the course of the past 9 years.

Public health obesity prevention experts have recently emphasized a policy systems and environmental change approach. Absent, however, are studies describing how practitioners transition from policy adoption to implementation. In the realm of food policy, financing programs to incentivize healthy food retail development in communities classified as “underserved” are underway at the local, state, and national levels. Implementing these policies requires a clear definition of eligibility for program applicants and policy administrators. This article outlines a methodology to establish eligibility for healthy food financing programs by describing the work of The Food Trust to coadminister programs in 3 distinct regions. To determine program eligibility, qualitative assessments of community fit are needed and national data sources must be locally verified. Our findings have broad implications for programs that assess need to allocate limited public/private financing resources.

Modified ground-truthing: an accurate and cost-effective food environment validation method for town and rural areas

Background

A major concern in food environment research is the lack of accuracy in commercial business listings of food stores, which are convenient and commonly used. Accuracy concerns may be particularly pronounced in rural areas. Ground-truthing or on-site verification has been deemed the necessary standard to validate business listings, but researchers perceive this process to be costly and time-consuming. This study calculated the accuracy and cost of ground-truthing three town/rural areas in Minnesota, USA (an area of 564 miles, or 908 km), and simulated a modified validation process to increase efficiency without comprising accuracy. For traditional ground-truthing, all streets in the study area were driven, while the route and geographic coordinates of food stores were recorded.

Results

The process required 1510 miles (2430 km) of driving and 114 staff hours. The ground-truthed list of stores was compared with commercial business listings, which had an average positive predictive value (PPV) of 0.57 and sensitivity of 0.62 across the three sites. Using observations from the field, a modified process was proposed in which only the streets located within central commercial clusters (the 1/8 mile or 200 m buffer around any cluster of 2 stores) would be validated. Modified ground-truthing would have yielded an estimated PPV of 1.00 and sensitivity of 0.95, and would have resulted in a reduction in approximately 88 % of the mileage costs.

Conclusions

We conclude that ground-truthing is necessary in town/rural settings. The modified ground-truthing process, with excellent accuracy at a fraction of the costs, suggests a new standard and warrants further evaluation.

Scale effects in food environment research: Implications from assessing socioeconomic dimensions of supermarket accessibility in an eight-county region of South Carolina

Choice of neighborhood scale affects associations between environmental attributes and health-related outcomes. This phenomenon, a part of the modifiable areal unit problem, has been described fully in geography but not as it relates to food environment research. Using two administrative-based geographic boundaries (census tracts and block groups), supermarket geographic measures (density, cumulative opportunity and distance to nearest) were created to examine differences by scale and associations between three common U.S. Census-based socioeconomic status (SES) characteristics (median household income, percentage of population living below poverty and percentage of population with at least a high school education) and a summary neighborhood SES z-score in an eight-county region of South Carolina. General linear mixed-models were used. Overall, both supermarket density and cumulative opportunity were higher when using census tract boundaries compared to block groups. In analytic models, higher median household income was significantly associated with lower neighborhood supermarket density and lower cumulative opportunity using either the census tract or block group boundaries, and neighborhood poverty was positively associated with supermarket density and cumulative opportunity. Both median household income and percent high school education were positively associated with distance to nearest supermarket using either boundary definition, whereas neighborhood poverty had an inverse association. Findings from this study support the premise that supermarket measures can differ by choice of geographic scale and can influence associations between measures. Researchers should consider the most appropriate geographic scale carefully when conducting food environment studies.

The Built Food Environment and Dietary Intake among African-American Adults

OBJECTIVES

The built food environment surrounding people's homes may influence their dietary intake. This exploratory study examined how the density of different sources of food in the residential environment was associated with dietary consumption among 77 African-American adults in Houston, Texas.

METHODS

The number of fast-food-type restaurants, large grocery stores, and convenience-type stores within 2- and 5-mile residential buffers were divided by the respective areas to obtain food environment density variables. Intake of fruit and vegetables [FV], fiber [FI], and percent energy from fat [PEF] was assessed using National Health Interview Survey items. Covariate-adjusted regressions were used to assess relations of interest.

RESULTS

Greater density of fast-food-type restaurants within 2 miles was associated with greater FV, FI, and PEF (ps ≤ .012); and for FV and FI within 5 miles (ps ≤ .004). Density of large grocery stores was unrelated to intake. Greater density of convenience-type stores within 2 miles was negatively associated with FV and FI (ps ≤ .03); results became marginal at 5 miles for FV (p = .10) but not FI (p = .03).

CONCLUSION

Maximizing healthy offerings in venue-rich metropolitan areas might provide direction for policies to reduce obesity.

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

Background

Obesity 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.

Methods

This 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.

Results

For 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.

Conclusions

This 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.

Geographic measures of retail food outlets and perceived availability of healthy foods in neighbourhoods

OBJECTIVE

To examine associations between geographic measures of retail food outlets and perceived availability of healthy foods.

DESIGN

Cross-sectional.

SETTING

A predominantly rural, eight-county region of South Carolina, USA.

SUBJECTS

Data from 705 household shoppers were analysed using ordinary least-squares regression to examine relationships between geographic measures (presence and distance) of food outlets obtained via a geographic information system and perceived availability of healthy foods (fresh fruits and vegetables and low-fat foods).

RESULTS

The presence of a supermarket within an 8·05 km (5-mile) buffer area was significantly associated with perceived availability of healthy foods (β=1·09, P=0·025) when controlling for all other food outlet types. However, no other derived geographic presence measures were significant predictors of perceived availability of healthy foods. Distances to the nearest supermarket (β=-0·16, P=0·003), dollar and variety store (β=-0·15, P=0·005) and fast-food restaurant (β=0·11, P=0·015) were all significantly associated with perceptions of healthy food availability.

CONCLUSIONS

Our results suggest that distance to food outlets is a significant predictor of healthy food perceptions, although presence is sensitive to boundary size. Our study contributes to the understanding and improvement of techniques that characterize individuals' food options in their community.

Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set

Background

The densities of food retailers, alcohol outlets, physical activity facilities, and medical facilities have been associated with diet, physical activity, and management of medical conditions. Most of the research, however, has relied on cross-sectional studies. In this paper, we assess methodological issues raised by a data source that is increasingly used to characterize change in the local business environment: the National Establishment Time Series (NETS) dataset.

Discussion

Longitudinal data, such as NETS, offer opportunities to assess how differential access to resources impacts population health, to consider correlations among multiple environmental influences across the life course, and to gain a better understanding of their interactions and cumulative health effects. Longitudinal data also introduce new data management, geoprocessing, and business categorization challenges. Examining geocoding accuracy and categorization over 21 years of data in 23 counties surrounding New York City (NY, USA), we find that health-related business environments change considerably over time. We note that re-geocoding data may improve spatial precision, particularly in early years. Our intent with this paper is to make future public health applications of NETS data more efficient, since the size and complexity of the data can be difficult to exploit fully within its 2-year data-licensing period. Further, standardized approaches to NETS and other “big data” will facilitate the veracity and comparability of results across studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1482-4) contains supplementary material, which is available to authorized users.

Food deserts or food swamps?: A mixed-methods study of local food environments in a Mexican city

Differential access to healthy foods has been hypothesized to contribute to disparities in eating behaviors and health outcomes. While food deserts have been researched extensively in developed Anglophone countries, evidence from low- and middle-income countries is still scarce. In Mexico, prevalence of obesity is among the highest worldwide. As obesity has increased nationally and become a widespread public health issue, it is becoming concentrated in the low-income population. This mixed-methods study uses a multidimensional approach to analyze food environments in a low-, middle-, and high-income community in a Mexican city. The study advances understanding of the role that food environments may play in shaping eating patterns by analyzing the density and proximity of food outlet types as well as the variety, quantity, quality, pricing, and promotion of different foods. These measures are combined with in-depth qualitative research with families in the communities, including photo elicitation, to assess perceptions of food access. The central aims of the research were to evaluate physical and economic access and exposure to healthy and unhealthy foods in communities of differing socioeconomic status as well as participants' subjective perceptions of such access and exposure. The findings suggest a need to reach beyond a narrow focus on food store types and the distance from residence to grocery stores when analyzing food access. Results show that excessive access and exposure to unhealthy foods and drinks, or "food swamps," may be a greater concern than food deserts for obesity-prevention policy in Mexico.

Food environments are relevant to recruitment and adherence in dietary modification trials

Few studies have examined the built environment's role in recruitment to and adherence in dietary intervention trials. Using data from a randomized dietary modification trial of urban Latina breast cancer survivors, we tested the hypotheses that neighborhood produce access could act as a potential barrier and/or facilitator to recruitment, and that a participant's produce availability would be associated with increased fruit/vegetable intake, one of the intervention's targets. Eligible women who lived within a higher produce environment had a non-significant trend towards being more likely to enroll in the trial. Among enrollees, women who had better neighborhood access to produce had a non-significant trend toward increasing fruit/vegetable consumption. As these were not a priori hypotheses to test, we consider these analyses to be hypothesis generating and not confirmatory. Results suggest that participants' food environment should be considered when recruiting to and assessing the adherence of dietary intervention studies.

Neighborhood fast food availability and fast food consumption

Recent nutritional and public health research has focused on how the availability of various types of food in a person's immediate area or neighborhood influences his or her food choices and eating habits. It has been theorized that people living in areas with a wealth of unhealthy fast-food options may show higher levels of fast-food consumption, a factor that often coincides with being overweight or obese. However, measuring food availability in a particular area is difficult to achieve consistently: there may be differences in the strict physical locations of food options as compared to how individuals perceive their personal food availability, and various studies may use either one or both of these measures. The aim of this study was to evaluate the association between weekly fast-food consumption and both a person's perceived availability of fast-food and an objective measure of fast-food presence - Geographic Information Systems (GIS) - within that person's neighborhood. A randomly selected population-based sample of eight counties in South Carolina was used to conduct a cross-sectional telephone survey assessing self-report fast-food consumption and perceived availability of fast food. GIS was used to determine the actual number of fast-food outlets within each participant's neighborhood. Using multinomial logistic regression analyses, we found that neither perceived availability nor GIS-based presence of fast-food was significantly associated with weekly fast-food consumption. Our findings indicate that availability might not be the dominant factor influencing fast-food consumption. We recommend using subjective availability measures and considering individual characteristics that could influence both perceived availability of fast food and its impact on fast-food consumption. If replicated, our findings suggest that interventions aimed at reducing fast-food consumption by limiting neighborhood fast-food availability might not be completely effective.

Do people really know what food retailers exist in their neighborhood? Examining GIS-based and perceived presence of retail food outlets in an eight-county region of South Carolina

Measures of neighborhood food environments have been linked to diet and obesity. However, the appropriate measurement methods and how people actually perceive their food environments are still unclear. In a cross-sectional study of 939 adults, the perceived presence of food outlets was compared to the geographic-based presence of outlets within a participant's neighborhood, utilizing percent agreement and Kappa statistics. Perceived presence was based on survey-administered questions, and geographic-based presence was characterized using 1-, 2-, 3- and 5-mile (1-mile=1.6km) Euclidean- and network-based buffers centered on each participant's residence. Analyses were also stratified by urban and non-urban designations. Overall, an individual's perceived neighborhood food environment was moderately correlated with the geographic-based presence of outlets. The performance of an individual's perception was most optimal using a 2- or 3-mile geographic-based neighborhood boundary and/or when the participant lived in a non-urban neighborhood. This study has implications for how researchers measure the food environment.

Diet and obesity in Los Angeles County 2007-2012: Is there a measurable effect of the 2008 "Fast-Food Ban"?

We evaluate the impact of the "Los Angeles Fast-Food Ban", a zoning regulation that has restricted opening/remodeling of standalone fast-food restaurants in South Los Angeles since 2008. Food retail permits issued after the ban are more often for small food/convenience stores and less often for larger restaurants not part of a chain in South Los Angeles compared to other areas; there are no significant differences in the share of new fast-food chain outlets, other chain restaurants, or large food markets. About 10% of food outlets are new since the regulation, but there is little evidence that the composition has changed differentially across areas. Data from the California Health Interview Survey show that fast-food consumption and overweight/obesity rates have increased from 2007 to 2011/2012 in all areas. The increase in the combined prevalence of overweight and obesity since the ban has been significantly larger in South Los Angeles than elsewhere. A positive development has been a drop in soft drink consumption since 2007, but that drop is of similar magnitude in all areas.

Evaluation of the placement of mobile fruit and vegetable vendors to alleviate food deserts in New York City

Introduction

In 2008, the New York City (NYC) health department licensed special mobile produce vendors (Green Carts) to increase access to fruits and vegetables in neighborhoods with the lowest reported fruit and vegetable consumption and the highest obesity rates. Because economic incentives may push vendors to locate in more trafficked, less produce-deprived areas, we examined characteristics of areas with and without Green Carts to explore whether Carts are positioned to reach the intended populations.

Methods

Using ArcGIS software, we mapped known NYC Green Cart locations noted through 2013 and generated a list of potential (candidate) sites where Carts could have located. We compared the food environment (via categorizing “healthy” or “unhealthy” food stores using federal classification codes corroborated by online storefront images) and other factors that might explain Cart location (eg, demographic, business, neighborhood characteristics) near actual and candidate sites descriptively and inferentially.

Results

Seven percent of Green Carts (n = 265) were in food deserts (no healthy stores within one-quarter mile) compared with 36% of candidate sites (n = 644, P < .001). Most Carts (78%) were near 2 or more healthy stores. Green Carts had nearly 60 times the odds of locating near subway stops (P < .001), were closer to large employers (odds ratio [OR], 6.4; P < .001), other food stores (OR, 14.1; P < .001), and in more populous tracts (OR, 2.9, P <.01) compared with candidate sites.

Conclusion

Green Carts were rarely in food deserts and usually had multiple healthy stores nearby, suggesting that Carts may not be serving the neediest neighborhoods. Exploration of Carts’ benefits in non–food desert areas is needed, but incentivizing vendors to locate in still-deprived places may increase program impact.

Differences in food environment perceptions and spatial attributes of food shopping between residents of low and high food access areas

OBJECTIVE

To explore potential differences in food shopping behaviors and healthy food availability perceptions between residents living in areas with low and high food access.

DESIGN

A cross-sectional telephone survey to assess food shopping behaviors and perceptions. Data from an 8-county food environment field census used to define the Centers for Disease Control and Prevention (CDC) healthier food retail tract and US Department of Agriculture Economic Research Service food desert measure.

PARTICIPANTS

A total of 968 residents in 8 South Carolina counties.

MAIN OUTCOME MEASURES

Residents' food shopping behaviors and healthy food availability perceptions.

ANALYSIS

Linear and logistic regression.

RESULTS

Compared with residents in high food access areas, residents in low food access areas traveled farther to their primary food store (US Department of Agriculture Economic Research Service: 8.8 vs 7.1 miles, P = .03; CDC: 9.2 vs 6.1 miles, P < .001), accumulated more total shopping miles per week (CDC: 28.0 vs 15.4 miles; P < .001), and showed differences in perceived healthy food availability (P < .001) and shopping access (P < .001).

CONCLUSIONS AND IMPLICATIONS

These findings lend support to ongoing community and policy interventions aimed at reducing food access disparities.

Do minority and poor neighborhoods have higher access to fast-food restaurants in the United States?

BACKGROUND

Disproportionate access to unhealthy foods in poor or minority neighborhoods may be a primary determinant of obesity disparities. We investigated whether fast-food access varies by Census block group (CBG) percent black and poverty.

METHODS

We measured the average driving distance from each CBG population-weighted centroid to the five closest top ten fast-food chains and CBG percent black and percent below poverty.

RESULTS

Among 209,091 CBGs analyzed (95.1% of all US CBGs), CBG percent black was positively associated with fast-food access controlling for population density and percent poverty (average distance to fast-food was 3.56 miles closer (95% CI: -3.64, -3.48) in CBGs with the highest versus lowest quartile of percentage of black residents). Poverty was not independently associated with fast-food access. The relationship between fast-food access and race was stronger in CBGs with higher levels of poverty (p for interaction <0.0001).

CONCLUSIONS

Predominantly black neighborhoods had higher access to fast-food while poverty was not an independent predictor of fast-food access.

Where are the food deserts? An evaluation of policy-relevant measures of community food access in South Carolina

Several recent United States (US) policies target spatial access to healthier food retailers. We evaluated two measures of community food access developed by two different agencies, using a 2009 food environment validation study in South Carolina as a reference. While the US Department of Agriculture Economic Research Service's (USDA ERS) measure designated 22.5% of census tracts as food deserts, the Centers for Disease Control and Prevention's (CDC) measure designated 29.0% as non-healthier retail tracts; 71% of tracts were designated consistently between USDA ERS and CDC. Our findings suggest a need for greater harmonization of these measures of community food access.

The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States

BACKGROUND

Food store availability may determine the quality of food consumed by residents. Neighborhood racial residential segregation, poverty, and urbanicity independently affect food store availability, but the interactions among them have not been studied.

PURPOSE

To examine availability of supermarkets, grocery stores, and convenience stores in US census tracts according to neighborhood racial/ethnic composition, poverty, and urbanicity.

METHODS

Data from 2000 US Census and 2001 InfoUSA food store data were combined and multivariate negative binomial regression models employed.

RESULTS

As neighborhood poverty increased, supermarket availability decreased and grocery and convenience stores increased, regardless of race/ethnicity. At equal levels of poverty, Black census tracts had the fewest supermarkets, White tracts had the most, and integrated tracts were intermediate. Hispanic census tracts had the most grocery stores at all levels of poverty. In rural census tracts, neither racial composition nor level of poverty predicted supermarket availability.

CONCLUSIONS

Neighborhood racial composition and neighborhood poverty are independently associated with food store availability. Poor predominantly Black neighborhoods face a double jeopardy with the most limited access to quality food and should be prioritized for interventions. These associations are not seen in rural areas which suggest that interventions should not be universal but developed locally.

Variation in low food access areas due to data source inaccuracies

Several spatial measures of community food access identifying so called "food deserts" have been developed based on geospatial information and commercially-available, secondary data listings of food retail outlets. It is not known how data inaccuracies influence the designation of Census tracts as areas of low access. This study replicated the U.S. Department of Agriculture Economic Research Service (USDA ERS) food desert measure and the Centers for Disease Control and Prevention (CDC) non-healthier food retail tract measure in two secondary data sources (InfoUSA and Dun & Bradstreet) and reference data from an eight-county field census covering169 Census tracts in South Carolina. For the USDA ERS food deserts measure accuracy statistics for secondary data sources were 94% concordance, 50-65% sensitivity, and 60-64% positive predictive value (PPV). Based on the CDC non-healthier food retail tracts both secondary data demonstrated 88-91% concordance, 80-86% sensitivity and 78-82% PPV. While inaccuracies in secondary data sources used to identify low food access areas may be acceptable for large-scale surveillance, verification with field work is advisable for local community efforts aimed at identifying and improving food access.

Environmental influences on fruit and vegetable intake: results from a path analytic model

OBJECTIVE

Fruit and vegetable (F&V) intake is influenced by behavioural and environmental factors, but these have rarely been assessed simultaneously. We aimed to quantify the relative influence of supermarket availability, perceptions of the food environment and shopping behaviour on F&V intake.

DESIGN

A cross-sectional study.

SETTING

Eight counties in South Carolina, USA, with verified locations of all supermarkets.

SUBJECTS

A telephone survey of 831 household food shoppers ascertained F&V intake with a seventeen-item screener, primary food store location, shopping frequency and perceptions of healthy food availability, and supermarket availability was calculated with a geographic information system. Path analysis was conducted. We report standardized beta coefficients on paths significant at the 0·05 level.

RESULTS

Frequency of grocery shopping at primary food store (β = 0·11) was the only factor exerting an independent, statistically significant direct effect on F&V intake. Supermarket availability was significantly associated with distance to utilized food store (β = -0·24) and shopping frequency (β = 0·10). Increased supermarket availability was significantly and positively related to perceived healthy food availability in the neighbourhood (β = 0·18) and ease of shopping access (β = 0·09). Collectively considering all model paths linked to perceived availability of healthy foods, this measure was the only other factor to have a significant total effect on F&V intake.

CONCLUSIONS

While the majority of the literature to date has suggested an independent and important role of supermarket availability for F&V intake, our study found only indirect effects of supermarket availability and suggests that food shopping frequency and perceptions of healthy food availability are two integral components of a network of influences on F&V intake.