Faculty Bibliography

Food and beverage marketing has been identified as a major driver of obesity yet sports sponsorship remains common practice and represents millions of dollars in advertising expenditures. Research shows that food and beverage products associated with sports (e.g., M&M's with National Association for Stock Car Auto Racing logo) generate positive feelings, excitement, and a positive self-image among adults and children. Despite this, self-regulatory pledges made by food companies to limit exposure of unhealthy products to children have not improved the nutritional quality of foods marketed to children. We reviewed the literature about sports-related food marketing, including food and beverage companies' use of sports sponsorships, athlete endorsements, and sports video games. This review demonstrates that sports sponsorships with food and beverage companies often promote energy-dense, nutrient-poor products and while many of these promotions do not explicitly target youth, sports-related marketing affects food perceptions and preferences among youth. Furthermore, endorsement of unhealthy products by professional athletes sends mixed messages; although athletes may promote physical activity, they simultaneously encourage consumption of unhealthy products that can lead to negative health outcomes. We argue that more athletes and sports organizations should stop promoting unhealthy foods and beverages and work with health experts to encourage healthy eating habits among youth.

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.

OBJECTIVE: Evidence on the effects of restaurant calorie labeling on consumer and restaurant behavior is mixed. This paper examined: (1) consumer responses to calorie information alone or compared to modified calorie information and (2) changes in restaurant offerings following or in advance of menu labeling implementation. METHODS: Searches were conducted in PubMed, Web of Science, Policy File, and PAIS International to identify restaurant calorie labeling studies through October 1, 2016, that measured calories ordered, consumed, or available for purchase on restaurant menus. The reference lists of calorie labeling articles were also searched. RESULTS: Fifty-three studies were included: 18 in real-world restaurants, 9 in cafeterias, and 21 in laboratory or simulation settings. Five examined restaurant offerings. CONCLUSIONS: Because of a lack of well-powered studies with strong designs, the degree to which menu labeling encourages lower-calorie purchases and whether that translates to a healthier population are unclear. Although there is limited evidence that menu labeling affects calories purchased at fast-food restaurants, some evidence demonstrates that it lowers calories purchased at certain types of restaurants and in cafeteria settings. The limited data on modified calorie labels find that such labels can encourage lower-calorie purchases but may not differ in effects relative to calorie labels alone.

The objective of this study was to examine the association between financial hardship, condomless anal intercourse and HIV risk among a sample of men who have sex with men (MSM). Users of a popular geosocial networking application in Paris were shown an advertisement with text encouraging them to complete a anonymous web-based survey (n = 580). In adjusted multivariate models, high financial hardship (compared to low financial hardship) was associated with engagement in condomless anal intercourse (aRR 1.28; 95% CI 1.08-1.52), engagement in condomless receptive anal intercourse (aRR 1.34; 95% CI 1.07-1.67), engagement in condomless insertive anal intercourse (aRR 1.30; 95% CI 1.01-1.67), engagement in transactional sex (aRR 2.36; 95% CI 1.47-3.79) and infection with non-HIV STIs (aRR 1.50; 95% CI 1.07-2.10). This study suggests that interventions to reduce financial hardships (e.g., income-based strategies to ensure meeting of basic necessities) could decrease sexual risk behaviors in MSM.

Previous studies have identified an association between socioeconomic status and sleep health. While some research has studied this association among sexual minority groups, including men who have sex with men (MSM), they exclusively focused on US-based populations. The interplay between the two in shaping sleep health has not been previously examined on populations residing outside the US. This study considers both determinants, by investigating whether financial hardship is associated with sleep health among a sample of MSM in Paris, France. Broadcast advertisements were placed on a popular geosocial-networking smartphone application for MSM to direct users in Paris to a web-based survey measuring financial hardship and five dimensions of sleep health as well as socio-demographic characteristics. Modified Poisson models with robust error variance were computed to estimate risk ratios (RRs) and 95% confidence intervals (CI) for the associations between financial hardship and the following self-reported outcomes: 1) poor sleep quality, 2) short sleep duration; and 3) sleep problems. In total, 580 respondents completed the survey. In this sample, both financial hardship and poor sleep health were common - 45.5% reported that it was extremely, very, or somewhat difficult for them to meet their monthly payments on bills (referred to as "high financial hardship") and 30.1% rated their sleep as fairly bad or very bad (referred to as "poor sleep quality"). Multivariate models revealed that, compared to participants who reported low financial hardship, those who reported high financial hardship were more likely to report poor sleep quality (aRR: 1.35, 95% CI: 1.04, 1.77), to report problems falling asleep (aRR: 1.23, 95% CI: 1.02, 1.49), and to report problems staying awake in the daytime (aRR: 3.12, 95% CI: 1.83, 5.31). Future research should investigate whether this relationship is causal and determine whether interventions to reduce financial hardships could promote sleep health among MSM.

OBJECTIVES: This study aimed to evaluate the acceptability of smartphone-based text message- and voice-based ecological momentary assessment (EMA) methods among a sample of low-income housing residents in New York City. Using data from the community-based NYC Low Income Housing, Neighborhoods and Health Study (n = 112), the acceptability of text message- and voice-based EMA methods were assessed via survey. RESULTS: Overall, 88.4% of participants reported that they would participate in a study that utilized text message-based EMA. These analyses showed no appreciable differences by sub-groups (p > .05). Overall, 80.2% of participants reported that they would participate in a study that used voice-based EMA. This voice-based method was least acceptable among participants younger than 25 years old compared to participants of all other ages, chi2(2) = 10.107, p = .006 (among the younger participants 60.7% reported "yes" regarding the anticipated acceptability of voice-based EMA and 39.3% reported "no"). Overall, this work suggests that text message- and voice-based EMA methods are acceptable for use among low-income housing residents. However, the association between age and the acceptability of voice-based EMA suggests that these methods may be less suited for younger populations.

Little is known about how neighborhood noise influences cardiovascular disease (CVD) risk among low-income populations. The aim of this study was to investigate associations between neighborhood noise complaints and body mass index (BMI) and blood pressure (BP) among low-income housing residents in New York City (NYC), including the use of global positioning system (GPS) data. Data came from the NYC Low-Income Housing, Neighborhoods and Health Study in 2014, including objectively measured BMI and BP data (N = 102, Black = 69%), and 1 week of GPS data. Noise reports from "NYC 311" were used to create a noise complaints density (unit: 1000 reports/km2) around participants' home and GPS-defined activity space neighborhoods. In fully-adjusted models, we examined associations of noise complaints density with BMI (kg/m2), and systolic and diastolic BP (mmHg), controlling for individual- and neighborhood-level socio-demographics. We found inverse relationships between home noise density and BMI (B = -2.7 [kg/m2], p = 0.009), and systolic BP (B = -5.3 mmHg, p = 0.008) in the fully-adjusted models, and diastolic BP (B = -3.9 mmHg, p = 0.013) in age-adjusted models. Using GPS-defined activity space neighborhoods, we observed inverse associations between noise density and systolic BP (B = -10.3 mmHg, p = 0.019) in fully-adjusted models and diastolic BP (B = -7.5 mmHg, p = 0.016) in age-adjusted model, but not with BMI. The inverse associations between neighborhood noise and CVD risk factors were unexpected. Further investigation is needed to determine if these results are affected by unobserved confounding (e.g., variations in walkability). Examining how noise could be related to CVD risk could inform effective neighborhood intervention programs for CVD risk reduction.

INTRODUCTION: Residents of some low-income neighborhoods have limited access to fresh fruits and vegetables. In 2008, New York City issued new mobile fruit and vegetable cart licenses for neighborhoods with inadequate availability of fresh produce. Some of these carts were equipped with electronic benefit transfer (EBT) machines, allowing them to accept Supplemental Nutrition Assistance Program (SNAP) benefits. This article examines the association between type and quantities of fruits and vegetables purchased from mobile fruit and vegetable vendors and consumer characteristics, including payment method. METHODS: Customers at 4 produce carts in the Bronx, New York, were surveyed during 3 periods in 2013 and 2014. Survey data, including purchased fruit and vegetable quantities, were analyzed using multivariable negative binomial regressions, with payment method (cash only vs EBT or EBT and cash) as the primary independent variable. Covariates included availability of EBT, vendor, and customer sociodemographic characteristics. RESULTS: A total of 779 adults participated in this study. Shoppers who used SNAP benefits purchased an average of 5.4 more cup equivalents of fruits and vegetables than did shoppers who paid with cash. Approximately 80% of this difference was due to higher quantities of purchased fruits. CONCLUSION: Expanding access to EBT machines at mobile produce carts may increase purchases of fruits and vegetables from these vendors.

BACKGROUND:This research evaluated the effects of financial incentives and purchase restrictions on food purchasing in a food benefit program for low income people. METHODS:Participants (n=279) were randomized to groups: 1) Incentive- 30% financial incentive for fruits and vegetables purchased with food benefits; 2) Restriction- no purchase of sugar-sweetened beverages, sweet baked goods, or candies with food benefits; 3) Incentive plus Restriction; or 4) Control- no incentive or restrictions. Participants received a study-specific debit card where funds were added monthly for 12-weeks. Food purchase receipts were collected over 16 weeks. Total dollars spent on grocery purchases and by targeted food categories were computed from receipts. Group differences were examined using general linear models. RESULTS:Weekly purchases of fruit significantly increased in the Incentive plus Restriction ($4.8) compared to the Restriction ($1.7) and Control ($2.1) groups (p <.01). Sugar-sweetened beverage purchases significantly decreased in the Incentive plus Restriction (-$0.8 per week) and Restriction ($-1.4 per week) groups compared to the Control group (+$1.5; p< .0001). Sweet baked goods purchases significantly decreased in the Restriction (-$0.70 per week) compared to the Control group (+$0.82 per week; p < .01). CONCLUSIONS:Paired financial incentives and restrictions on foods and beverages purchased with food program funds may support more healthful food purchases compared to no incentives or restrictions. CLINICAL TRIAL REGISTRATION:Clinicaltrials.gov Identifier: NCT02643576 .

By mid-2018, federal policy will require chain restaurants with more than 20 U.S. locations to include calorie information on their menus. Despite high expectations that this policy would encourage healthier eating, most studies of local policies to mandate calorie labels have demonstrated little impact on consumer choice. In this article, the authors adapt Burton and Kees's (2012) conceptual framework for eating behavior change to better understand the limited impact of these policies thus far. Using two surveys of fast-food consumers in Philadelphia, the authors estimate the percentage who might reasonably be expected to respond to calorie labels given the requirements of the Burton and Kees model. They find that as few as 8% of fast-food consumers meet all the model's requirements and, therefore, would be expected to change their eating behavior as a result of calorie information. The authors use the model and findings to consider how calorie-labeling policy could be improved for greater impact.