Faculty Bibliography

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.

BACKGROUND:Exposure to food advertisements is associated with poor diet among youth, and food and beverage companies are increasingly advertising on social media sites that are popular among youth. OBJECTIVE:To identify the prevalence of social media advertising among fast food, beverage, and snack companies and examine advertising techniques they use on Instagram, Facebook, Twitter, Tumblr, and Vine. METHODS:We quantified the increase in the creation of social media accounts from 2007 to 2016 among 200 fast food, beverage, and snack brands from the United States. We conducted content analyses to examine the marketing themes and healthfulness of products featured in 2000 posts from a subset of 20 brands and used multilevel regression to assess associations between marketing themes (eg, adolescents socializing) and interactive tools (eg, hashtags). RESULTS:Two hundred brands collectively managed 568 accounts in 2016. Content analyses revealed that unique social media features (eg, geo-tags) appeared in 74.5% (n = 1489) of posts, and 31.5% (n = 630) were interactive. Posts featuring adolescents were more likely to be interactive than posts featuring adults (P < 0.001). Two-thirds (67.9%; n = 362) of foods shown were unhealthy, and 61.2% (n = 435) of beverages were sugar sweetened. CONCLUSIONS:Social media food advertising is pervasive and uses interactive tools to engage with users.

Pricing incentives may reduce disparities in obesity among Supplemental Nutrition Assistance Program (SNAP) participants by increasing fruit and vegetable purchases. However, few studies have evaluated the feasibility and effectiveness of those incentives in supermarkets, as opposed to farmers markets. In 2015 and 2016, as part of a US Department of Agriculture (USDA) pilot program, a dollar-matching program in Michigan provided SNAP participants with a subsidy on fresh produce purchases. Using data on millions of individual transactions from thirty-two stores, we found that SNAP participants' spending on fresh produce was significantly higher at stores that implemented the subsidy than at control stores during both intervention periods (7.4 percent and 2.2 percent higher in 2015 and 2016, respectively). Our results highlight the effectiveness and feasibility of dollar-matching programs for fruit and vegetable purchases by SNAP participants who shop at supermarkets, and they support the USDA's expansion of existing programs to that setting in additional states.

Readers should note the following two typographical errors in this article.

The objective of this study was to measure change in obesity prevalence among New York City (NYC) adults from 2004 to 2013-2014 and assess variation across sociodemographic subgroups. We used objectively measured height and weight data from the NYC Health and Nutrition Examination Survey to calculate relative percent change in obesity (≥ 30 kg/m²) between 2004 (n = 1987) and 2013-2014 (n = 1489) among all NYC adults and sociodemographic subgroups. We also examined changes in self-reported proxies for energy imbalance. Estimates were age-standardized and statistical significance was evaluated using two-tailed T tests and multivariable regression (p < 0.05). Between 2004 and 2013-2014, obesity increased from 27.5 to 32.4% (p = 0.01). Prevalence remained stable and high among women (31.2 to 32.8%, p = 0.53), but increased among men (23.4 to 32.0%, p = 0.002), especially among non-Latino White men and men age ≥ 65 years. Black adults had the highest prevalence in 2013-2014 (37.1%) and Asian adults experienced the largest increase (20.1 to 29.2%, p = 0.06), especially Asian women. Foreign-born participants and participants lacking health insurance also had large increases in obesity. We observed increases in eating out and screen time over time and no improvements in physical activity. Our findings show increases in obesity in NYC in the past decade, with important sociodemographic differences.