Comparing nutrition environments in bodegas and fast-food restaurants

Assessing the healthiness of menus of all out-of-home food outlets and its socioeconomic patterns in Great Britain

Food environment research predominantly focuses on the spatial distribution of out-of-home food outlets. However, the healthiness of food choices available within these outlets has been understudied, largely due to resource constraints. In this study, we propose an innovative, low-resource approach to characterise the healthiness of out-of-home food outlets at scale. Menu healthiness scores were calculated for food outlets on JustEat, and a deep learning model was trained to predict these scores for all physical out-of-home outlets in Great Britain, based on outlet names. Our findings highlight the "double burden" of the unhealthy food environment in deprived areas where there tend to be more out-of-home food outlets, and these outlets tend to be less healthy. This methodological advancement provides a nuanced understanding of out-of-home food environments, with potential for automation and broad geographic application.

Dietary contributions of food outlets by urbanization level in the US population aged 2 years and older-NHANES 2013-2018

BACKGROUND

Differences in food access, availability, affordability, and dietary intake are influenced by the food environment, which includes outlets where foods are obtained. These differences between food outlets within rural and urban food environments in the United States are not well understood.

OBJECTIVES

The aim of this analysis is to describe the contribution of foods and beverages from 6 outlets-grocery stores, convenience stores, full-service restaurants, quick-service restaurants, schools, and other outlets-to the total energy intake and Healthy Eating Index (HEI)-2015 scores in the United States population, by urbanization level (nonmetropolitan statistical areas [MSAs], small-to-medium MSAs, and large MSAs).

METHODS

Data from the National Health and Nutrition Examination Survey 2013-2018 were used. Dietary intake from one 24-h dietary recall was analyzed by the outlet where a food or beverage was obtained and by urbanization. Linear regression, adjusted for sex, age, race and Hispanic origin, and family income, was used to predict the contribution of each food outlet to the total energy intake and HEI-2015 total and component scores by urbanization level.

RESULTS

During 2013-2018, foods and beverages from grocery stores and quick-service and full-service restaurants contributed to 62.1%, 15.1%, and 8.5% of the energy intake, respectively. The percentage of energy intake from full- and quick-service restaurants increased with increasing urbanization level. HEI-2015 total scores increased with the increasing urbanization level overall (48.1 non-MSAs, 49.2 small-to-medium MSAs, and 51.3 large MSAs) for grocery stores (46.7 non-MSAs, 48.0 small-to-medium MSAs, and 50.6 large MSAs) and for quick-service restaurants (35.8 non-MSAs, 36.3 small-to-medium MSAs, and 37.5 large MSAs).

CONCLUSIONS

Grocery stores and restaurants were the largest contributors of energy intake in urban and rural areas. Diet quality improved with increasing urbanization overall and for grocery stores and quick-service restaurants.

Ethnic Restaurant Nutrition Environments and Cardiovascular Health: Examining Hispanic Caribbean Restaurants in New York City

Objective

To adapt and apply the Nutrition Environment Measures Survey for Restaurants (NEMS-R) to Hispanic Caribbean (HC) restaurants and examine associations between restaurant characteristics and nutrition environment measures.

Methods

We adapted the NEMS-R for HC cuisines (Cuban, Puerto Rican, Dominican) and cardiovascular health-promoting factors, and applied the instrument (NEMS-HCR) to a random sample of HC restaurants in New York City (NYC) (N=89). Multivariable linear regression was used to assess independent associations between NEMS-HCR score and restaurant characteristics (cuisine, size, type [counter-style vs sit-down] and price).

Results

None of the menus in the restaurants studied listed any main dishes as "healthy" or "light." More than half (52%) offered mostly (>75%) nonfried main dishes, and 76% offered at least one vegetarian option. The most common facilitator to healthy eating was offering reduced portion sizes (21%) and the most common barrier was having salt shakers on tables (40%). NEMS-HCR scores (100-point scale) ranged from 24.1-55.2 (mean=39.7). In multivariable analyses, scores were significantly related to cuisine (with Puerto Rican cuisine scoring lower than Cuban and Dominican cuisines), and size (with small [<22 seats] restaurants scoring lower than larger restaurants). We found a significant quadratic association with midpoint price, suggesting that scores increased with increasing price in the lowest price range, did not vary in the middle range, and decreased with increasing price in the highest range.

Conclusions

Our application of the NEMS-R to HC restaurants in NYC revealed areas for potential future interventions to improve food offerings and environmental cues to encourage healthful choices.

Relationship between retail food outlets near public schools and adolescent obesity in New York City

Using objectively-measured height and weight data from academic years 2009-2013 (n = 1,114,010 student-year observations), we estimated the association between the food outlet in closest proximity to schools and the likelihood of obesity among New York City public high school students. Obesity risk was higher for students with a corner store as the nearest option to schools, regardless of whether other food outlet types were located within a quarter mile or a half mile of schools (i.e., benchmarks for zoning policies). Policymakers may want to consider introducing healthier food options near schools, in conjunction with programs to support changes within corner stores.

Disparities in trajectories of changes in the unhealthy food environment in New York City: A latent class growth analysis, 1990-2010

Disparities in availability of food retailers in the residential environment may help explain racial/ethnic and socio-economic differences in obesity risk. Research is needed that describes whether food environment dynamics may contribute to equalizing conditions across neighborhoods or to amplifying existing inequalities over time. This study improves the understanding of how the BMI-unhealthy food environment has evolved over time in New York City. We use longitudinal census tract-level data from the National Establishment Time-Series (NETS) for New York City in the period 1990-2010 and implement latent class growth analysis (LCGA) to (1) examine trajectories of change in the number of unhealthy food outlets (characterized as selling calorie-dense foods such as pizza and pastries) at the census tract-level, and (2) examine how trajectories are related to socio-demographic characteristics of the census tract. Overall, the number of BMI-unhealthy food outlets increased between 1990 and 2010. We summarized trajectories of evolutions with a 5-class model that indicates a pattern of fanning out, such that census tracts with a higher initial number of BMI-unhealthy food outlets in 1990 experienced a more rapid increase over time. Finally, fully adjusted logistic regression models reveal a greater increase in BMI-unhealthy food outlets in census tracts with: higher baseline population size, lower baseline income, and lower proportion of Black residents. Greater BMI-unhealthy food outlet increases were also noted in the context of census tracts change suggestive of urbanization (increasing population density) or increasing purchasing power (increasing income).

Sources of Foods That Are Ready-to-Consume ('Grazing Environments') Versus Requiring Additional Preparation ('Grocery Environments'): Implications for Food-Environment Research and Community Health

Local businesses that offer foods may create different 'grazing environments' (characterized by sources of ready-to-consume foods) and 'grocery environments' (characterized by source of foods for later preparation). Such environments may be relevant to different populations at different times and may vary by neighborhood. In neighborhoods within two demographically distinct areas of the Bronx, NY [Area A (higher-poverty, greater minority representation, lesser vehicle ownership) vs. Area B], researchers assessed all storefront businesses for food offerings. Food offerings could be ready-to-consume or require additional preparation. 'Healthful' offerings included fruits and vegetables, whole grains, and nuts; 'less-healthful' offerings included 'refined sweets' and 'salty/fatty fare.' 'Food businesses' (those primarily focused on selling food) were distinguished from 'other businesses' (not focused primarily on food selling). Area A had a higher percentage of street segments on which foods were available (28.6% vs. 6.9% in Area B; difference 21.7% points [95% CI 17.0, 26.5]) and a higher percentage of businesses offering foods (46.9% vs. 41.7% in Area B; difference 5.2% points [95% CI - 2.0, 12.4]). 'Less-healthful' items predominated in both 'grazing environments' and overall environments ('grazing' plus 'grocery environments'; the environments researchers typically measure) in both Areas A and B. 'Other businesses' represented about 2/3 of all businesses and accounted for nearly 1/3 of all the businesses offering food in both geographic areas. The lower-income area with greater minority representation and less private transportation had more businesses offering foods on more streets. There was near-perfect overlap between 'grazing environments' and overall environments in both geographic areas. Future research should consider the extent of 'grazing' and 'grocery environments,' and when each might be most relevant to populations of interest.

Measures of the food environment: A systematic review of the field, 2007-2015

BACKGROUND

Many studies have examined the relationship between the food environment and health-related outcomes, but fewer consider the integrity of measures used to assess the food environment. The present review builds on and makes comparisons with a previous review examining food environment measures and expands the previous review to include a more in depth examination of reliability and validity of measures and study designs employed.

METHODS

We conducted a systematic review of studies measuring the food environment published between 2007 and 2015. We identified these articles through: PubMed, Embase, Web of Science, PsycINFO, and Global Health databases; tables of contents of relevant journals; and the National Cancer Institute's Measures of the Food Environment website. This search yielded 11,928 citations. We retained and abstracted data from 432 studies.

RESULTS

The most common methodology used to study the food environment was geographic analysis (65% of articles) and the domination of this methodology has persisted since the last review. Only 25.9% of studies in this review reported the reliability of measures and 28.2% reported validity, but this was an improvement as compared to the earlier review. Very few of the studies reported construct validity. Studies reporting measures of the school or worksite environment have decreased since the previous review. Only 13.9% of the studies used a longitudinal design.

CONCLUSIONS

To strengthen research examining the relationship between the food environment and population health, there is a need for robust and psychometrically-sound measures and more sophisticated study designs.

Neighborhood Disparities in the Restaurant Food Environment

IMPORTANCE

Restaurant meals account for a significant portion of the American diet. Investigating disparities in the restaurant food environment can inform targeted interventions to increase opportunities for healthy eating among those who need them most.

OBJECTIVE

To examine neighborhood disparities in restaurant density and the nutrition environment within restaurants among a statewide sample of Wisconsin households.

METHODS

Households (N = 259) were selected from the 2009-2010 Survey of the Health of Wisconsin (SHOW), a population-based survey of Wisconsin adults. Restaurants in the household neighborhood were enumerated and audited using the Nutrition Environment Measures Survey for Restaurants (NEMS-R). Neighborhoods were defined as a 2- and 5-mile street-distance buffer around households in urban and non-urban areas, respectively. Adjusted linear regression models identified independent associations between sociodemographic household characteristics and neighborhood restaurant density and nutrition environment scores.

RESULTS

On average, each neighborhood contained approximately 26 restaurants. On average, restaurants obtained 36.1% of the total nutrition environment points. After adjusting for household characteristics, higher restaurant density was associated with both younger and older household average age (P < .05), all white households (P = .01), and urban location (P < .001). Compared to rural neighborhoods, urban and suburban neighborhoods had slightly higher (ie, healthier) nutrition environment scores (P < .001).

CONCLUSIONS AND RELEVANCE

The restaurant food environment in Wisconsin neighborhoods varies by age, race, and urbanicity, but offers ample room for improvement across socioeconomic groups and urbanicity levels. Future research must identify policy and environmental interventions to promote healthy eating in all restaurants, especially in young and/or rural neighborhoods in Wisconsin.

Prepared Food Availability in U.S. Food Stores: A National Study

INTRODUCTION

Prepared, ready-to-eat foods comprise a significant part of Americans' diets and are increasingly obtained from food stores. Yet, little is known about the availability and healthfulness of prepared, ready-to-eat food offerings at stores. This study examines associations among community characteristics (racial/ethnic composition, poverty level, urbanicity) and availability of both healthier and less-healthy prepared foods in U.S. supermarkets, grocery stores, and convenience stores.

METHODS

Observational data were collected from 4,361 stores in 317 communities spanning 42 states in 2011 and 2012. Prepared food availability was assessed via one healthier food (salads or salad bar), three less-healthy items (pizza, hot dog/hamburger, taco/burrito/taquito), and one cold sandwich item. In 2014, multivariable generalized linear models were used to test associations with community characteristics.

RESULTS

Overall, 63.6% of stores sold prepared foods, with 20.0% offering prepared salads and 36.4% offering at least one less-healthy item. Rural stores were 26% less likely to carry prepared salads (prevalence ratio [PR]=0.74, 95% CI=0.62, 0.88) and 14% more likely to carry at least one less-healthy prepared food item (PR=1.14, 95% CI=1.00, 1.30). Convenience stores in high-poverty communities were less likely to carry prepared salads than those in low-poverty communities (PR=0.64, 95% CI=0.47, 0.87). Among supermarkets, prepared salads were more likely to be carried in majority-white, low-poverty communities than in non-white, high-poverty communities.

CONCLUSIONS

Increasing the healthfulness of prepared foods within stores may offer an important opportunity to improve the food environment.

Small Convenience Stores and the Local Food Environment: An Analysis of Resident Shopping Behavior Using Multilevel Modeling

PURPOSE

Local food environments can influence the diet and health of individuals through food availability, proximity to retail stores, pricing, and promotion. This study focused on how small convenience stores, known in New York City as bodegas, influence resident shopping behavior and the food environment.

DESIGN

Using a cross-sectional design, 171 bodegas and 2118 shoppers were sampled.

SETTING

Small convenience stores in New York City.

SUBJECTS

Any bodega shopper aged 18+ who purchased food or beverage from a participating store.

MEASURES

Data collection consisted of a store assessment, a health and behavior survey given to exiting customers, and a bag check that recorded product information for all customer purchases.

ANALYSIS

Descriptive statistics were generated for bodega store characteristics, shopper demographics, and purchase behavior. Multilevel models were used to assess the influence of product availability, placement, and advertising on consumer purchases of sugar-sweetened beverages (SSBs), water, and fruits and vegetables.

RESULTS

Seventy-one percent of participants reported shopping at bodegas five or more times per week, and 35% reported purchasing all or most of their monthly food allotment at bodegas. Model results indicated that lower amounts of available fresh produce were significantly and independently associated with a higher likelihood of SSB purchases. A second, stratified multilevel model showed that the likelihood of purchasing an SSB increased with decreasing varieties of produce when produce was located at the front of the store. No significant effects were found for water placement and beverage advertising.

CONCLUSIONS

Small convenience stores in New York City are an easily accessible source of foods and beverages. Bodegas may be suitable for interventions designed to improve food choice and diet.