Association of community food environment and obesity among US adults: a geographical information system analysis

Social inequities in food deserts and food swamps in a northeastern Brazilian capital

This study identified food deserts and swamps, investigating their associations with socioeconomic and demographic conditions. This ecological study was conducted using data from urban census tracts in the city of Recife, which were considered the unit of analysis. Information on food retail was obtained from government sources in 2019. Census tracts below the 25th percentile in the density of healthy food retail (i.e., those that predominantly sell natural or minimally processed foods, mixed businesses, and super- and hypermarkets) were classified as food deserts. Census tracts above the 25th percentile in the density of unhealthy food retail (i.e., those selling primarily ultra-processed foods) were considered food swamps. The socioeconomic and demographic conditions of the census tracts were evaluated using variables from the 2010 census (per capita income, average income, race, literacy of the head of household, and the availability of essential services) and the Health Vulnerability Index. Census tracts considered food deserts (28.5%) were more vulnerable, characterized by lower income and access to essential services, more illiterate residents and more minorities (Black/Indigenous/mixed race). Food swamps (73.47%) were more prevalent in less vulnerable neighbourhoods characterized by higher percentages of literate residents and Whites, greater purchasing power, and better basic sanitation. The characteristics of Recife's food deserts and swamps demonstrate social inequalities in the food environment. Public facilities could play a vital role in promoting healthy eating within food deserts. Additionally, future implementation of taxes on ultra-processed foods and the provision of tax subsidies to natural or minimally processed food sellers might contribute to fostering healthier dietary choices.

Food deserts exposure, density of fast-food restaurants, and park access: Exploring the association of food and recreation environments with obesity and diabetes using global and local regression models

To prevent obesity and diabetes environmental interventions such as eliminating food deserts, restricting proliferation of food swamps, and improving park access are essential. In the United States, however, studies that examine the food and park access relationship with obesity and diabetes using both global and local regression are lacking. To guide county, state, and federal policy in combating obesity and diabetes, there is a need for cross-scale analyses to identify that relationship at national and local levels. This study applied spatial regression and geographically weighted regression to the 3,108 counties in the contiguous United States. Global regression show food deserts exposure and density of fast-food restaurants have non-significant association with obesity and diabetes while park access has a significant inverse association with both diseases. Geographically weighted regression that takes into account spatial heterogeneity shows that, among southern states that show high prevalence of obesity and diabetes, Alabama and Mississippi stand out as having opportunity to improve park access. Results suggest food deserts exposure are positively associated with obesity and diabetes in counties close to Alabama, Georgia, and Tennessee while density of fast-food restaurants show positive association with two diseases in counties of western New York and northwestern Pennsylvania. These findings will help policymakers and public health agencies in determining which geographic areas need to be prioritized when implementing public interventions such as promoting healthy food access, limiting unhealthy food options, and increasing park access.

Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments

BACKGROUND

The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understanding contextual determinants, the resources provided by technological advances could become a key factor in obesogenic environment research. This study aims to identify different sources of non-traditional data and their applications, considering the domains of obesogenic environments: physical, sociocultural, political and economic.

METHODS

We conducted a systematic search in PubMed, Scopus and LILACS databases by two independent groups of reviewers, from September to December 2021. We included those studies oriented to adult obesity research using non-traditional data sources, published in the last 5 years in English, Spanish or Portuguese. The overall reporting followed the PRISMA guidelines.

RESULTS

The initial search yielded 1583 articles, 94 articles were kept for full-text screening, and 53 studies met the eligibility criteria and were included. We extracted information about countries of origin, study design, observation units, obesity-related outcomes, environment variables, and non-traditional data sources used. Our results revealed that most of the studies originated from high-income countries (86.54%) and used geospatial data within a GIS (76.67%), social networks (16.67%), and digital devices (11.66%) as data sources. Geospatial data were the most utilised data source and mainly contributed to the study of the physical domains of obesogenic environments, followed by social networks providing data to the analysis of the sociocultural domain. A gap in the literature exploring the political domain of environments was also evident.

CONCLUSION

The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.

The association of unhealthy and healthy food store accessibility with obesity prevalence among adults in the Netherlands: A spatial analysis

Introduction

Obesity prevalence has almost tripled in Europe since 1980, and the obesogenic (food) environment is hypothesised to be one of the main drivers. Still, empirical evidence is rare for Europe.

Objective

This ecological study explores spatial patterns of obesity prevalence of adults (aged 19+) in the Netherlands in 2016. It studies, in particular, its global associations with (un)healthy food store accessibility while assessing local differences and evaluating the importance of the immediate versus the wider food surroundings.

Methods

In our ecological study, we used small-area estimated obesity prevalence (adults, aged 19+) from 2836 neighbourhoods (six-digit postal codes, wijken) and combined this with measures from Statistics Netherlands on accessibility to (unhealthy) fast food and (healthy) fresh food. Spatial lag of X (SLX) models were estimated for the entire Netherlands to explore global associations. Separate models for urban, suburban, and rural neighbourhoods and a geographically weighted regression (GWR) were estimated to explore and visualise local variations in the associations. Total associations from the SLX models were then decomposed to yield contributions of the immediate and wider food surroundings.

Results

Regional clusters of high obesity were observed in selected areas in the north-east, the south-west, and south-east. Limited accessibility to unhealthy food was globally associated with lower obesity prevalence, whereas better accessibility to fresh food stores and supermarkets was not. The association regarding worse accessibility to unhealthy food was strongest for urban neighbourhoods, especially for the Randstad region. In urban settings, also better accessibility to fresh food stores proved relevant. The wider food surrounding proved more important than the immediate food surrounding, throughout.

Discussion

Public policies addressing obesity might be more effective when reducing the presence of unhealthy food rather than expanding healthy food supply. Moreover, they should focus on urban regions and high obesity clusters, thereby considering wider food surroundings.

Differential Associations Between Changes in Food Environment and Changes in BMI Among Adults Living in Urban, Low-Income Communities

BACKGROUND

Food environments can contribute to excess weight gain among adults, but the evidence is mixed.

OBJECTIVES

This longitudinal study investigated the associations between changes in the food environment and changes in BMI in adults and whether changes in the food environment differentially impact various subgroups.

METHODS

At 2 time points, BMI was calculated using self-reported height and weight data from 517 adults (mean age, 41 years) living in 4 New Jersey cities. The counts of different types of food outlets within 0.4, 0.8, and 1.6 km of respondents' residences were collected at baseline and tracked until follow-up. A binary measure of social standing (social-advantage group, n = 219; social-disadvantage group, n = 298) was created through a latent class analysis using social, economic, and demographic variables. Multivariable linear regression modeled the associations between changes in BMI with measures of the food environment; additionally, interaction terms between the measures of food environment and social standing were examined.

RESULTS

Overall, over 18 months, an increase in the number of small grocery stores within 0.4 km of a respondent's residence was associated with a decrease in BMI (β = -1.0; 95% CI: -1.9, -0.1; P = 0.024), while an increase in the number of fast-food restaurants within 1.6 km was associated with an increase in BMI (β = 0.1; 95% CI: 0.01, 0.2; P = 0.027). These overall findings, however, masked some group-specific associations. Interaction analyses suggested that associations between changes in the food environment and changes in BMI varied by social standing. For instance, the association between changes in fast-food restaurants and changes in BMI was only observed in the social-disadvantage group (β = 0.1; 95% CI: 0.02, 0.2; P = 0.021).

CONCLUSIONS

In a sample of adults living in New Jersey, changes in the food environment had differential effects on individuals' BMIs, based on their social standing.

Enhancing the Retail Food Environment Index (RFEI) with Neighborhood Commuting Patterns: A Hybrid Human-Environment Measure

The Retail Food Environment Index (RFEI) and its variants have been widely used in public health to measure people's accessibility to healthy food. These indices are purely environmental as they only concern the geographic distribution of food retailers, but fail to include human factors, such as demographics, socio-economy, and mobility, which also shape the food environment. The exclusion of human factors limits the explanatory power of RFEIs in identifying neighborhoods of the greatest concern. In this study, we first proposed a hybrid approach to integrate human and environmental factors into the RFEI. We then demonstrated this approach by incorporating neighborhood commuting patterns into a traditional RFEI: we devised a multi-origin RFEI (MO_RFEI) that allows people to access food from both homes and workplaces, and further an enhanced RFEI (eRFEI) that allows people to access food with different transportation modes. We compared the traditional and proposed RFEIs in a case study of Florida, USA, and found that the eRFEI identified fewer and more clustered underserved populations, allowing policymakers to intervene more effectively. The eRFEI depicts more realistic human shopping behaviors and better represents the food environment. Our study enriches the literature by offering a new and generic approach for assimilating a neighborhood context into food environment measures.

Spatial spillovers, living environment and obesity in France: Evidence from a spatial econometric framework

In 2019, obesity affected 17% of French adults. In this article, we use a unique data set that combines individual-level health and consumption data with living environment data (food, sports and health amenities). We develop a spatial econometric framework to address French health disparities in obesity prevalence across space. We find that regulations on fast food restaurant locations could be a policy instrument to counter the prevalence of obesity. We also establish the existence of spatial spillovers of sports and medical amenities on obesity. This new evidence points to the need to consider a wider context than just the immediate local environment in the fight against the obesity pandemic.

Associations between retail food environment and the nutritional quality of food purchases in French households: The Mont’Panier cross-sectional study

Purpose

The purpose of this study was to assess whether the retail food environment, measured by multiple indicators around the home and in activity space, was associated with the nutritional quality of food purchases.

Methods

This cross-sectional study included 462 households from a quota sampling survey conducted in the south of France (Montpellier Metropolitan Area). The revised Healthy Purchase Index was implemented in order to assess the nutritional quality of food purchases. Food environment indicators (presence, number, relative density and proximity of food outlets) were calculated around the home and in activity space using a geographical information system. Six different types of food outlets were studied: supermarkets, markets, greengrocers, bakeries, other specialized food stores (butcher’s, fishmonger’s and dairy stores) and small grocery stores. Associations between food environment and the nutritional quality of food purchases were assessed using multilevel models, and geographically weighted regressions to account for spatial non-stationarity. Models were adjusted for households’ socioeconomic and demographic characteristics.

Results

The nutritional quality of food purchases was positively associated with the number of greengrocers around the home (1 vs. 0: β = 0.25, 95%CI = [0.01, 0.49]; >1 vs. 0: β = 0.25, 95%CI = [0.00, 0.50]), but negatively associated with the number of markets around the home (1 vs. 0: β = -0.20, 95%CI = [-0.40, 0.00]; >1 vs. 0: β = -0.37, 95%CI = [-0.69, -0.06]). These associations varied across space in the area studied. For lower income households, the number of greengrocers in activity space was positively associated with the nutritional quality of food purchases (1 vs. 0: β = 0.70, 95%CI = [0.12, 1.3]; >1 vs. 0: β = 0.67, 95%CI = [0.22, 1.1]).

Conclusions

Greengrocers might be an effective type of food store for promoting healthier dietary behaviors. Further studies, particularly interventional studies, are needed to confirm these results in order to guide public health policies in actions designed to improve the food environment.

What is the availability, affordability, and quality of foods and beverages aligned with dietary guidance in Louisiana Supplemental Nutrition Assistance Program (SNAP) authorized stores?

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SNAP stores in Louisiana score low on measures of healthy food access.

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No differences in healthy food access were found between rural/urban SNAP stores.

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Independent SNAP stores scored lower on healthy food access than corporate stores.

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SNAP grocery and dollar stores scored higher than SNAP convenience stores.

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Healthy retail partnerships with independent SNAP retailers are needed in Louisiana.

Healthy food retail strategies are delivered by Cooperative Extension Services in Louisiana to improve public health among communities with lower income. To guide Cooperative Extension Services Programming, the aim of this study was to assess healthy food access among SNAP-authorized stores. This included comparing the availability, affordability, and quality of healthy foods sold in these stores by geography, ownership, and store type. Seventy-five Louisiana SNAP-authorized stores were selected for measurement. Between October 2019 and March 2020 (prior to the COVID-19 national emergency declaration), trained researchers used the Nutrition Environment Measures Survey in Stores (NEMS-S) to assess the availability, affordability, and quality of healthy versus less healthy foods and beverages in 42 SNAP-authorized stores, including: grocery (n = 12, 29%), convenience (n = 17, 41%), drug (n = 1, 2%), dollar (n = 11, 26%), and butcher/meat (n = 1, 2%). Multivariate analysis of variance (a priori, p < 0.05) determined if differences in total NEMS-S scores or subscores existed by geography (urban versus rural), ownership (corporate/chain versus independent), or store type. No urban/rural differences were identified. Corporate/chain SNAP-authorized stores scored higher on average than independent SNAP-authorized stores for the total NEMS-S score (17.2 versus 8.1; p = 0.009) and availability subscore (13.1 versus 6.1; p = 0.02). SNAP-authorized grocery stores scored higher than all other store types (total NEMS-S score 27.6), followed by SNAP-authorized dollar stores (total NEMS-S score 10.7), and SNAP-authorized convenience stores (total NEMS-S score 5) (p < 0.001). Louisiana Cooperative Extension Services should explore ways to scale healthy food retail strategies statewide with a specific emphasis on independent and smaller SNAP-authorized retailers.

Study on Spatial Structure Characteristics of the Tourism and Leisure Industry

By taking Beijing as the case site, using open-source Point of Interest data, and employing spatial visualization techniques, this study explores the spatial structural characteristics of the Beijing tourism and leisure industry and its sub-sectors. It has been found that (1) the nearest neighbor indexes of the tourism and leisure industry and its sub-sectors are all less than 1, indicating that the tourism and leisure industry and its sub-sectors in Beijing exhibit a spatial clustering distribution. Scenic spots have the largest R-value of 0.52 and, thus, the lowest degree of clustering. The minimum R-value of 0.15 is found in catering, marking the highest degree of clustering in the industry; (2) the main directional trend of the tourism and leisure industry and its sub-sectors in Beijing is the “northeast-southwest” direction, the south-north directional dispersion is dominant, and scenic spots demonstrate a more noticeable trend of spatial dispersion; (3) within the area from Sanlitun Street in the north to Panjiayuan Street in the south, and from Chaoyangmen Street in the west to Liulitun Street in the east, is situated the largest portion of cluster centers with the highest degree of clustering in Beijing’s tourism and leisure industry. The contiguous high-density cluster center of catering starts from Sanlitun Street in the north to Jinsong Street in the south, and from Chaoyangmen Street in the west to Liulitun Street in the east. The cluster of shopping and entertainment shows a checkerboard pattern in the CZCF and NUDZ. The high-value cluster of accommodation occurs primarily around Sanlitun, Panjiayuan, and Qianmen; (4) the distribution of three grades of hot spot areas and non-significant areas of tourism and leisure, catering, accommodation, and shopping and entertainment in Beijing demonstrates a circular pattern that centers around the CZCF and expands outward in sequence. High-value hot spot streets for this area are dominated by Beixinqiao Street, Hepingli Street, Sanlitun Street, Heping Street, and Tuanjiehu Street; and the high-value cold spot streets of the area are chiefly in Fuzizhuang Township, Wangping Town, Miaofeng Mountain Town, and Tanzhesi Town.

Associations between density and quality of health promotion programmes and built environment features across Jerusalem

BACKGROUND

Health promotion programmes (HPPs) have the potential to influence individual health, depending on their quality and characteristics. Little is known about how they interact with built environment features and neighbourhood demographics in cities with substantial health disparities.

METHODS

Using the European Quality Instrument for Health Promotion (EQUIHP), we assessed the quality of HPPs, operating between 2016 and 2017, among adults aged 18-75 in Jerusalem. Areas were characterized by ethnicity and area socioeconomic level. Health information (body mass index, physical activity level) was obtained from the city profile survey. Geospatial information on the location and length of walking paths and bicycle lanes was obtained. Spearman correlations were used to assess associations among variables.

RESULTS

Ninety-three HPPs operating in 349 locations in Jerusalem were identified. Programmes were unevenly distributed across urban planning areas (UPAs), with the highest density observed in the southwest, areas populated mainly by non-orthodox Jewish residents. However, the best performing HPPs based on EQUIHP score were in the north and east UPAs, inhabited primarily by Arab residents. At a neighbourhood level, characteristics of the built environment positively correlated with higher total EQUIHP scores: the ratio between walking lane length to the neighbourhood's population size (r = 0.413, P < 0.001) and length of bicycle lane per population (r = 0.309, P = 0.5). Median EQUIHP score negatively correlated with the number of programmes per neighbourhood size (m2) (r = -0.327, P = 0.006) and neighbourhood average socioeconomic status (SES; r = -0.266, P = 0.027).

CONCLUSIONS

Our findings suggest that higher quality HPPs were preferentially located in areas of lower SES and served minority populations in Jerusalem.

Geographical heterogeneity across England in associations between the neighbourhood built environment and body mass index

Effects of residential neighbourhood environments on health may vary across geographical space, with differences in local contexts influencing how much a given neighbourhood characteristic matters for the health of local residents. Linking UK Biobank data from 302,952 urban-dwelling adults in England, collected between 2006 and 2010, to publicly available Local Authority-level data, we examined (a) whether cross-sectional associations between body mass index (BMI) and two characteristics of the neighbourhood built environment (availability of formal physical activity facilities near home, and fast-food proximity) vary by Local Authority (LA), and (b) whether cross-level interactions with LA-level physical features (natural landcover) and socio-cultural attributes (local obesity norms) reveal evidence of effect modification by these features of the wider contexts in which neighbourhoods are located. We found variation across urban England in the relationship between availability of neighbourhood formal physical activity facilities and BMI, and some evidence suggesting this association was stronger among people living in areas with less natural landcover, especially in areas outside of London. We also found that the relationship between proximity of fast-food stores to people's homes and BMI varied geographically across England. Local descriptive obesity norms were not an important modifier of this association. This paper highlights the importance of considering potential geographical heterogeneity in relationships between the built environment and health, and the implications for generalisability of research findings. By seeking to better understand sources of geographical heterogeneity, we may be able to better adapt and target built environment interventions for population health improvement.

A rapid review of stocking and marketing practices used to sell sugar-sweetened beverages in U.S. food stores

Sugar-sweetened beverages (SSBs) are a primary source of added sugars in the American diet. Habitual SSB consumption is associated with obesity and noncommunicable disease and is one factor contributing to U.S. health disparities. Public health responses to address marketing-mix and choice-architecture (MMCA) strategies used to sell SSB products may be required. Thus, our goal was to identify original research about stocking and marketing practices used to sell SSB in U.S. food stores. We used Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the World Health Organization (WHO) protocol for rapid reviewing. We searched six databases and Google Scholar using key terms focused on store type and SSB products. We characterized results using an MMCA framework with categories place, profile, portion, pricing, promotion, priming or prompting, and proximity. Our search resulted in the identification of 29 articles. Most results focused on profile (e.g., SSB availability) (n = 13), pricing (e.g., SSB prices or discounts) (n = 13), or promotion (e.g., SSB advertisements) (n = 13) strategies. We found some evidence of targeted MMCA practices toward at-risk consumers and differences by store format, such as increased SSB prominence among supermarkets. The potential for systematic variations in MMCA strategies used to sell SSB requires more research. We discuss implications for public health, health equity, and environmental sustainability.

Cancer-related Beliefs and Preventive Health Practices among Residents of Rural versus Urban Counties in Alabama

Higher prevalence of cancer-related risk factors, for example, tobacco use, obesity, poor diet, and physical inactivity, is observed in the U.S. Deep South and likely contributes to its increased cancer burden. While this region is largely rural, it is unknown whether cancer-related beliefs and lifestyle practices differ by rural-urban status or are more influenced by other factors. We contacted 5,633 Alabamians to complete a cross-sectional survey to discern cancer-related beliefs and lifestyle practices, and compared data from respondents residing in rural- versus urban-designated counties. Findings were summarized using descriptive statistics; rural-urban subgroups were compared using two-tailed, χ ² and t tests. Multivariable logistic regression models were used to explore associations by rural-urban status and other sociodemographic factors. Surveys were completed by 671 rural- and 183 urban-county respondents (15.2% response rate). Overall, the prevalence for overweight and obesity (77.8%) and sugar-sweetened beverage intake (273-364 calories/day) was higher than national levels. Most respondents (58%) endorsed raising the state tobacco tax. Respondents from rural- versus urban-designated counties were significantly more likely to be racial/ethnic minority, have lower education, employment, income, food security, and internet access, and endorse fatalistic cancer-related beliefs (<0.05; although regression models suggested that cancer belief differences are more strongly associated with education than counties of residence). Lifestyle practices were similar among rural-urban subgroups. Few rural-urban differences in cancer-related beliefs and lifestyle practices were found among survey respondents, although the high overall prevalence of fatalistic health beliefs and suboptimal lifestyle behaviors suggests a need for statewide cancer prevention campaigns and policies, including increased tobacco taxation.Prevention Relevance: Cancer incidence and mortality are higher in the U.S. Deep South, likely due to increased tobacco-use, obesity, poor diet, and physical inactivity. This study explores whether cancer-related beliefs and lifestyle practices differ by rural-urban status or other sociodemographic factors in a random sample of 855 residents across Alabama.

Food Addiction and Psychosocial Adversity: Biological Embedding, Contextual Factors, and Public Health Implications

The role of stress, trauma, and adversity particularly early in life has been identified as a contributing factor in both drug and food addictions. While links between traumatic stress and substance use disorders are well documented, the pathways to food addiction and obesity are less established. This review focuses on psychosocial and neurobiological factors that may increase risk for addiction-like behaviors and ultimately increase BMI over the lifespan. Early childhood and adolescent adversity can induce long-lasting alterations in the glucocorticoid and dopamine systems that lead to increased addiction vulnerability later in life. Allostatic load, the hypothalamic-pituitary-adrenal axis, and emerging data on epigenetics in the context of biological embedding are highlighted. A conceptual model for food addiction is proposed, which integrates data on the biological embedding of adversity as well as upstream psychological, social, and environmental factors. Dietary restraint as a feature of disordered eating is discussed as an important contextual factor related to food addiction. Discussion of various public health and policy considerations are based on the concept that improved knowledge of biopsychosocial mechanisms contributing to food addiction may decrease stigma associated with obesity and disordered eating behavior.

Rural Stroke Patients Have Higher Mortality: An Improvement Opportunity for Rural Emergency Medical Services Systems

PURPOSE

Early recognition and prompt prehospital care is a cornerstone of acute stroke treatment. Residents of rural areas have worse access to stroke services than urban residents. The purpose of this study was to (1) describe US trends in rural-urban stroke mortality and (2) identify possible factors associated with rural-urban stroke case-fatality disparities.

METHODS

This study was a nationwide retrospective cohort study of stroke admissions. The primary exposure was rurality of patient's residence. The primary outcome was death during hospital encounter. The secondary outcome was discharge to a care facility or home healthcare. Univariable and multivariable logistic regressions estimated the odds of mortality by subject rurality among stroke subjects.

FINDINGS

Rural stroke subjects had higher mortality than nonrural counterparts (18.6% rural vs 16.9% nonrural). After adjustment for patient and hospital factors, patient rurality was associated with increased odds of mortality (aOR = 1.11; 95% CI: 1.06-1.15; P < .001). For the secondary outcome of discharge to home, rural stroke subjects were less likely to be discharged to a care facility than nonrural stroke visits (aOR 0.94; 95% CI: 0.91-0.97; P < .001). Results were similar after adjusting for thrombolytics administration and transfer status.

CONCLUSIONS

Rural stroke patients have higher mortality than their urban counterparts likely due to their increased burden of chronic disease, lower health literacy, and reduced access to prompt prehospital care. There may be an opportunity for emergency medical services systems to assist in increasing stroke awareness for both patients and clinicians and to establish response patterns to expedite emergency care.

Neighborhood Environments, SNAP-Ed Eligibility, and Health Behaviors: An Analysis of the California Health Interview Survey (CHIS)

Neighborhood conditions are associated with health outcomes, but whether individual health behaviors are independent of or associated with the settings are not clear. We analyzed the California Health Interview Survey (CHIS) (N = 11,152) data to determine if the perceptions and behaviors of similar individuals with an income low enough to be eligible for SNAP-Ed services differed based on whether they lived in high- or low-income neighborhoods. We found that SNAP-Ed eligible individuals living in low-income neighborhoods walked for transportation more frequently (3.04 times versus 2.38 times, p = 0.001), drank sugary beverages more frequently in the past month (2.93 times versus 1.69 times, p = 0.000), and had a higher risk of obesity than similar low-income individuals living in high-income neighborhoods (0.34 versus 0.26, p = 0.012).

Supplemental Nutrition Assistance Program (SNAP)-Authorized Grocery, Convenience, Dollar, and Restaurant or Delivery Service Settings Are Associated With Increased Obesity Prevalence in Virginia

PURPOSE

United States Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants use SNAP-authorized stores for dietary purchases. Relationships between obesity prevalence and access to grocery and varied nontraditional (eg, dollar, drug, and convenience) SNAP settings are underexplored. This research aimed to determine the association of a full range of SNAP-authorized stores with obesity prevalence in Virginia.

DESIGN

The SNAP Retailer Locator was used to cross-sectionally identify authorized stores, and county health ranking information was applied based on store location.

SETTING

Virginia, United States.

SAMPLE

The SNAP-authorized stores, classified among store categories: grocery or supermarket; drug; mass merchandiser; supercenter; convenience; dollar; club; other; nonfood store; farmers markets; and independent grocery stores.

MEASURES

County-level obesity prevalence with income and rurality as potential confounders.

ANALYSIS

Multiple linear regression was used to determine associations between county-level adult obesity prevalence and available SNAP-authorized store formats (P < .05 a priori).

RESULTS

Store format was a predictor of obesity prevalence in Virginia in simple and adjusted models (R ² = 0.035, P < .0001 and R ² = 0.434, P < .0001, respectively). Grocery store or supermarket access was associated with obesity. The SNAP-authorized convenience, dollar, and nonfood stores were associated with a 0.3, 0.5, and 1.3 increase in county obesity prevalence, respectively (P < .05).

CONCLUSIONS

Research, practice, and health policy approaches to improve grocery, convenience, dollar, and restaurant or delivery service settings may favorably influence community obesity prevalence in Virginia.

Spatial Clusters of Diabetes and Physical Inactivity: Do Neighborhood Characteristics in High and Low Clusters Differ?

This study aims to find spatial clusters of diabetes and physical inactivity among a sample population in Kerala, India, and evaluate built environment characteristics within the high and low spatial clusters. Spatial clusters with a higher and lower likelihood of diabetes and physical inactivity were identified using spatial scan statistic at various radii. Built environment characteristics were captured at panchayat level and 1600 m buffer around participant location using Geographical Information Systems. Comparison of sociodemographic and built environment factors was carried out for participants within high and low spatial clusters using t tests. Ten high and 8 low spatial clusters of diabetes and 17 high and 23 low spatial clusters of physical inactivity were identified in urban and rural areas of Kerala. Significant differences in built environment characteristics were consistent for low spatial clusters of diabetes and physical inactivity in the urban scenario. Built environment characteristics were found to be relevant in both urban and rural areas of Kerala. There is an urgent call to explore spatial clustering of non-communicable diseases in Kerala and undo the one-size-fits-all approach for prevention and control of non-communicable diseases.