Faculty Bibliography

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.

Research has examined how the food environment affects the risk of cardiovascular disease (CVD). Many studies have focused on residential neighbourhoods, neglecting the activity spaces of individuals. The objective of this study was to investigate whether food environments in both residential and global positioning system (GPS)-defined activity space buffers are associated with body mass index (BMI) and blood pressure (BP) among low-income adults. Data came from the New York City Low Income Housing, Neighborhoods and Health Study, including BMI and BP data (n=102, age=39.3±14.1 years), and one week of GPS data. Five food environment variables around residential and GPS buffers included: fast-food restaurants, wait-service restaurants, corner stores, grocery stores, and supermarkets. We examined associations between food environments and BMI, systolic and diastolic BP, controlling for individual- and neighbourhood-level sociodemographics and population density. Within residential buffers, a higher grocery store density was associated with lower BMI (β=- 0.20 kg/m2, P<0.05), and systolic and diastolic BP (β =-1.16 mm Hg; and β=-1.02 mm Hg, P<0.01, respectively). In contrast, a higher supermarket density was associated with higher systolic and diastolic BP (β=1.74 mm Hg, P<0.05; and β=1.68, P<0.01, respectively) within residential buffers. In GPS neighbourhoods, no associations were documented. Examining how food environments are associated with CVD risk and how differences in relationships vary by buffer types have the potential to shed light on determinants of CVD risk. Further research is needed to investigate these relationships, including refined measures of spatial accessibility/exposure, considering individual's mobility.

The purpose of this research was to examine whether the local food environment, specifically the distance to the nearest sugar sweetened beverage (SSB) vendor, a measure of SSB availability and accessibility, was correlated with the likelihood of self-reported SSB consumption among a sample of fast food consumers. As part of a broader SSB behavior study in 2013-2014, respondents were surveyed outside of major chain fast food restaurants in New York City (NYC). Respondents were asked for the intersection closest to their home and how frequently they consume SSBs. Comprehensive, administrative food outlet databases were used to geo-locate the SSB vendor closest to the respondents' home intersections. We then used a logistic regression model to estimate the association between the distance to the nearest SSB vendor (overall and by type) and the likelihood of daily SSB consumption. Our results show that proximity to the nearest SSB vendor was not statistically significantly associated with the likelihood of daily SSB consumption, regardless of type of vendor. Our results are robust to alternative model specifications, including replacing the linear minimum distance measure with count of the total number of SSB vendors or presence of a SSB vendor within a buffer around respondents' home intersections. We conclude that there is not a strong relationship between proximity to nearest SSB vendor, or proximity to a specific type of SSB vendor, and frequency of self-reported SSB consumption among fast food consumers in NYC. This suggests that policymakers focus on alternative strategies to curtail SSB consumption, such as improving the within-store food environment or taxing SSBs.

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.

INTRODUCTION/BACKGROUND:Understanding what influences where food outlets locate is important for mitigating disparities in access to healthy food outlets. However, few studies have examined how neighborhood characteristics influence the neighborhood food environment over time, and whether these relationships differ by neighborhood-level income. METHODS:(density) of food outlets within real estate-derived neighborhoods. Associations were examined with lagged neighborhood-level sociodemographics and lagged density of food outlets, with interaction terms for neighborhood-level income. Data were analyzed in 2016. RESULTS:Neighborhood-level income at earlier years was negatively associated with the current density of convenience stores (β= -0.27, 95% CI= -0.16, -0.38, p<0.001). The percentage of neighborhood white population was negatively associated with fast food restaurant density in low-income neighborhoods (10th percentile of income: β= -0.17, 95% CI= -0.34, -0.002, p=0.05), and the density of smaller grocery stores across all income levels (β= -0.27, 95% CI= -0.45, -0.09, p=0.003). There was a lack of policy-relevant associations between the pre-existing food environment and the current density of food outlet types, including supermarkets. CONCLUSIONS:Socioeconomically disadvantaged and minority populations may attract "unhealthy" food outlets over time. To support equal access to healthy food outlets, the availability of "less healthy" food outlets types may be relatively more important than the potential lack of supermarkets or full-service restaurants.

BACKGROUND:Little is known about how diet-related and activity-related amenities relate to residential location behaviour. Understanding these relationships is essential for addressing residential self-selection bias. METHODS:Using 25 years (6 examinations) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (n=11 013 observations) and linked neighbourhood-level data from the 4 CARDIA baseline cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California, USA), we characterised participants' neighbourhoods as having low, average or high road connectivity and amenities using non-hierarchical cluster analysis. We then used repeated measures multinomial logistic regression with random effects to examine the associations between individual-level sociodemographics and neighbourhood-level characteristics with residential neighbourhood types over the 25-year period, and whether these associations differed by individual-level income. RESULTS:Being female was positively associated with living in neighbourhoods with low (vs high) road connectivity and activity-related and diet-related amenities among high-income individuals only. At all income levels, a higher percentage of neighbourhood white population and neighbourhood population <18 years were associated with living in neighbourhoods with low (vs high) connectivity and amenities. Individual-level race; age; and educational attainment, neighbourhood socioeconomic status and housing prices did not influence residential location behaviour related to neighbourhood connectivity and amenities at any income level. CONCLUSIONS:Neighbourhood-level factors appeared to play a comparatively greater role in shaping residential location behaviour than individual-level sociodemographics. Our study is an important step in understanding how residential locational behaviour relates to amenities and physical activity opportunities, and may help mitigate residential self-selection bias in built environment studies.