Faculty Bibliography

Several U.S. jurisdictions have adopted policies requiring healthy beverage defaults on children's menus, but it is unknown whether such policies or restrictions leads to fewer calories ordered. We recruited 479 caregivers of children for an online choice experiment and instructed participants to order dinner for their youngest child (2-6 years) from two restaurant menus. Participants were randomly assigned to one type of menu: 1) standard beverages on children's menus (Control; n = 155); 2) healthy beverages on children's menus (water, milk, or 100% juice), with unhealthy beverages available as substitutions (Default; n = 162); or 3) healthy beverages on children's menus, with no unhealthy beverage substitutions (Restriction; n = 162). We used linear regression with bootstrapping to examine differences between conditions in calories ordered from beverages. Secondary outcomes included percent of participants ordering unhealthy beverages (full-calorie soda, diet soda, and/or sugar-sweetened fruit drinks) and calories from unhealthy beverages. Calories ordered from beverages did not differ across conditions at Chili's [Default: 97.6 (SD = 69.8); p = 0.82; Restriction: 102.7 (SD = 71.5); p = 0.99; Control: 99.4 (SD = 72.7)] or McDonald's [Default: 90.2 (SD = 89.1); p = 0.55; Restriction: 89.0 (SD = 81.0); p = 0.94; Control: 96.5 (SD = 95.2)]. There were no differences in the percent of orders or calories ordered from unhealthy beverages. Though Restriction participants ordered fewer calories from full-calorie soda [(3.0 (SD = 21.6)] relative to Control participants [13.4 (SD = 52.1); p = 0.04)] at Chili's, we observed no such difference between Default and Control participants, or across McDonald's conditions. Overall, there was no effect of healthy default beverages or restrictions in reducing total calories ordered from unhealthy beverages for children in our experiment.

Sugary drinks and processed foods are associated with negative health outcomes in adults, including weight gain, and their consumption should be limited. However, they may be difficult to avoid if they are ubiquitously available in the retail environment. This study aimed to quantify the availability of such products for sale throughout New York City (NYC) at both food and non-food retailers. In 2018, ten one-mile retail-dense NYC street segments were selected for the sample. Data collectors canvassed each segment and visited all retailers, recording the type (food/non-food) and presence of processed food and beverages for sale. Descriptive statistics were analyzed for availability of products sold in retailers overall and by retailer type. In total, 491 retailers were identified (191 food, 300 non-food). Sugary drinks were available at 83% of food retailers and 19% of non-food retailers, while processed foods were available at 61% of food retailers and 16% of non-food retailers. Eighty-five percent of food retailers and 21% of non-food retailers sold sugary drinks and/or processed foods. This study supports and builds on results of previous research examining the availability of food and beverages in the retail environment. Sugary drinks and processed foods are ubiquitous at food and non-food retailers, providing pervasive cues to consume energy-dense, nutrient-poor products. Restrictions on where such products can be sold merit consideration.

INTRODUCTION/BACKGROUND:Previous research on sugar-sweetened beverage trends has focused on self-reported consumption from surveys. Few studies used objective store sales or explored differences by area-level demographics and store type. METHODS:The average volume of beverages sold per store per 3-digit zoning improvement plan code from 2006 to 2015 was calculated using national Nielsen Retail Scanner point-of-sale data from 24,240 stores. A multilevel regression model analyzed annual trends, with random intercepts for state and separate models for beverage type (regular soda, no/low-calorie soda, other sugary drinks, 100% fruit juice, bottled water). Differences by store type (convenience, supermarkets, drug stores, mass merchandisers) and area-level demographics (categorized as tertiles) were examined. Data were analyzed in 2019. RESULTS:The model-based estimates indicated that sales of regular soda (-11.8%), no/low-calorie soda (-19.8%), and 100% fruit juice (-31.9%) decreased over time, whereas sales of bottled water (+34.4%) increased and sales of other sugary drinks remained stable (+2.4%). Decreases in sugar-sweetened beverage sales were largely concentrated in supermarkets and larger in areas with high income and education levels and a high percentage of black and Hispanic people. There were also relatively larger increases in bottled water sales in states located in the South and Midwest. CONCLUSIONS:The finding that sales of sugar-sweetened beverages decreased over time, whereas sales of bottled water increased is encouraging because sugar-sweetened beverage consumption is linked to obesity and other chronic conditions. This study provides a novel, rigorous assessment of U.S. beverage sales trends and differences by community and store characteristics.

OBJECTIVE:The food retail environment is an important determinant of food access and the ability to achieve a healthy diet. However, immigrant communities may procure their food in different ways than the mainstream population owing to preferences for specific cultural products or limited English language proficiency. The objective of this analysis was to describe the grocery shopping patterns and behaviours of one of the largest immigrant groups in New York City, Chinese Americans - a group experiencing high poverty and cardio-metabolic disparities. DESIGN/METHODS:Cross-sectional survey data. SETTING/METHODS:Community-based sample. PARTICIPANTS/METHODS:Self-identified Chinese Americans in the New York metropolitan area (n 239). RESULTS:Three shopping patterns were identified: type 1: shopped weekly at an ethnic grocery store - and nowhere else; type 2: shopped weekly at a non-ethnic grocery store, with occasional shopping at an ethnic store and type 3: did not perform weekly shopping. Type 1 v. type 2 shoppers tended to have lower education levels (37·5 v. 78·0 % with college degree); to be on public insurance (57·6 v. 22·8 %); speak English less well (18·4 v. 41·4 %); be food insecure (47·2 v. 24·2 %; P < 0·01 for all) and to travel nearly two miles further to shop at their primary grocery store (β = -1·55; 95 % CI -2·81, -0·30). DISCUSSION/CONCLUSIONS:There are distinct grocery shopping patterns amongst urban-dwelling Chinese Americans corresponding to demographic and sociocultural factors that may help inform health interventions in this understudied group. Similar patterns may exist among other immigrant groups, lending preliminary support for an alternative conceptualisation of how immigrant communities interact with the food retail environment.

OBJECTIVE:Mobile produce markets (MPM) offering Supplemental Nutrition Assistance Program (SNAP) incentive programmes have the potential to provide accessible and affordable fruits and vegetables (FV) to populations at risk of food insecurity. The objective of this study is to characterise the customer base of an MPM and describe their participation at twelve market sites serving low-income seniors. DESIGN/METHODS:In 2018, customers from an MPM in Rhode Island (RI) participated in a cross-sectional survey (n 330; 68 % response rate), which measured dietary patterns, food security and food shopping behaviours. We compared the shopping habits and market experiences of customers who currently received SNAP benefits with those who did not currently receive SNAP benefits. SETTING/METHODS:An MPM in RI which offers a 50 % discount for FV purchased with SNAP benefits. PARTICIPANTS/METHODS:This study describes current market customers at twelve market sites serving low-income seniors. RESULTS:Market customers were mostly low-income, female, over the age of 50 years and Hispanic/Latino. Most customers received SNAP benefits, and almost half were food insecure. In addition, three quarters of SNAP customers reported their SNAP benefits last longer since shopping at the markets. Mixed logistic regression models indicated that SNAP customers were more likely to report buying and eating more FV than non-SNAP customers. CONCLUSIONS:MPM are critical resources of affordable produce and have been successful in improving access to FV among individuals of low socio-economic status in RI. This case study can inform policy and programme recommendations for MPM and SNAP incentive programmes.

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.

Using data from the United States Behavioral Risk Factor Surveillance System (2003-2012; N = 3,397,124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations.

: Background: To determine how many adolescents follow food/beverage brands on Instagram and Twitter, and examine associations between brands' youth-targeted marketing practices and percentages of adolescent followers.

OBJECTIVE:Researchers have linked geographic disparities in obesity to community-level characteristics, yet many prior observational studies have ignored temporality and potential for bias. METHODS:Repeated cross-sectional data were used from the Behavioral Risk Factor Surveillance System (BRFSS) (2003-2012) to examine the influence of county-level characteristics (active commuting, unemployment, percentage of limited-service restaurants and convenience stores) on BMI. Each exposure was calculated using mean values over the 5-year period prior to BMI measurement; values were standardized; and then variables were decomposed into (1) county means from 2003 to 2012 and (2) county-mean-centered values for each year. Cross-sectional (between-county) and longitudinal (within-county) associations were estimated using a random-effects within-between model, adjusting for individual characteristics, survey method, and year, with nested random intercepts for county-years within counties within states. RESULTS:(95% CI: -0.72 to -0.31) decrease in BMI over time. CONCLUSIONS:These results suggest that community-level characteristics play an important role in shaping geographic disparities in BMI between and within communities over time.