Faculty Bibliography

INTRODUCTION/BACKGROUND:Social media is the most prominent source of online food and beverage advertisements (ads) seen by adolescents. Companies target adolescent social media users with ads that feature calorie-dense, nutrient-poor products, and exposure to ads drives poor diet and risk for future diet-related diseases. Black, Hispanic and lower socio-economic status youth are exposed to significantly more ads than White peers. Several state-level policies in the USA have passed restricting youth from accessing social media without parental approval, and some policies have banned advertising to youth. This protocol paper describes a current study that aims to understand the impact of such policies in two states, Louisiana and Texas, as they were among the first to be implemented with racially/ethnically diverse populations. METHODS AND ANALYSIS/METHODS:This study employs a repeated cross-sectional difference-in-difference design in which 700 youth ages 13-17 years are being recruited each year for 5 years (Louisiana n=175, Texas n=175, matched comparisons from other states n=350). Youth screen record their mobile devices for 60 minutes while they browse social media platforms (eg, TikTok, Instagram) or use the internet. They also complete a brief survey about a variety of topics (eg, health behaviours, mental health). Adolescents are compensated for screen recording ($75) and the survey ($25). Study team members are coding recordings for several characteristics, including media platforms used, appearances of food or beverages, and food or beverage type. We will estimate the impact of policies on food and beverage ads seen per hour using Ordinary Least Squares regression models and heterogeneity-robust standard errors clustered at the state level (by year and cumulatively). We will run additional models with interaction terms with income and race/ethnicity, separately, to test the role of the policies on health disparities. ETHICS AND DISSEMINATION/BACKGROUND:Study procedures have been approved by the Institutional Review Board of the NYU Grossman School of Medicine. We will distribute findings in peer-reviewed journals and at local and national conferences. To complement traditional dissemination pathways, we will create infographics to share with relevant community stakeholders. We will also share findings with policymakers in states that have passed or considered similar policies.

OBJECTIVE:This study examined racial and ethnic differences in percent total weight loss (%TWL) and glycemic improvement following sleeve gastrectomy (SG) and explored the role of socioeconomic and psychosocial factors in postsurgical outcomes. METHODS:This longitudinal study included patients who underwent SG between 2017 and 2020, with follow-up visits over 24 months. RESULTS:Non-Hispanic Black (NHB) participants had lower %TWL at 3, 12, and 24 months compared with Hispanic (H) and non-Hispanic White (NHW) participants. Fat mass index was initially lower in NHB, with smaller reductions over time and significant group differences persisting at 24 months. NHB participants had higher baseline fat-free mass index values; by 24 months, fat-free mass index values were lower in H participants. Hemoglobin A1c decreased across all groups but remained consistently higher in NHB and H compared with NHW at 24 months. NHB participants reported higher perceived discrimination, sleep disturbance, and perceived stress than H and NHW participants at all time points. Employment status predicted %TWL at 12 months. There was a significant interaction between race and ethnicity and employment status observed at 12 and 24 months, suggesting that employment-related disparities could impact surgical outcomes. CONCLUSIONS:NHB participants experienced less favorable outcomes following SG, emphasizing the need for tailored interventions addressing socioeconomic and psychosocial disparities.

INTRODUCTION/BACKGROUND:Effective July 2018, the U.S. Department of Housing and Urban Development issued a rule requiring all public housing authorities to implement smoke-free housing (SFH) policies in their developments. We examined the differential impacts of SFH policy on hospitalizations for myocardial infarction (MI) and stroke among adults aged ≥50 years old living in New York City (NYC) Housing Authority (NYCHA) versus a matched-comparison population in NYC. AIMS AND METHODS/OBJECTIVE:We identified census block groups (CBGs) comprised solely of 100% NYCHA units (N = 160) and compared NYCHA CBGs to a selected subset of CBGs from all CBGs with no NYCHA units (N = 5646). We employed propensity score matching on distributions of key CBG-level sociodemographic and housing covariates. We constructed incident rates per 1000 persons by aggregating 3-month "quarterly" counts of New York State all-payer hospitalization data from October 2015 to December 2022 and dividing by the population aged ≥50 in selected CBGs, ascertained from 2016 American Community Survey 5-year estimates. We selected a difference-in-differences (DID) analytic approach to examine pre- and post-policy differences in incident hospitalizations between the intervention and matched-comparison groups. RESULTS:Matching results indicated a balanced match for all covariates, with standardized mean differences <0.10. In DID analyses, we observed small declines in both MI (DID = -0.26, p = .02) and stroke (DID = -0.28, p = .06) hospitalization rates for NYCHA CBGs compared to non-NYCHA CBGs from pre-to post-54 months' policy. CONCLUSIONS:SFH policies in NYC were associated with small reductions in CVD-related hospitalizations among older adults living in housing subject to the policy. IMPLICATIONS/CONCLUSIONS:Housing remains a key focal setting for interventions to reduce SHS exposure and associated morbidities. Ongoing monitoring is warranted to understand the long-term impacts of SFH policies in public housing developments.

OBJECTIVE:This study examined associations between access to leisure-time physical activity (LTPA) facilities and parks and repeated measures of glycated hemoglobin (A1C) over time, using follow-up tests among United States Veterans with newly diagnosed type-2 diabetes (T2D). METHODS:Data were analyzed from 274,463 patients in the Veterans Administration Diabetes Risk cohort who were newly diagnosed with T2D between 2008 and 2018 and followed through 2023. Generalized estimating equations with a logit link function and binomial logistic regression were used to examine associations. RESULTS:Patients were on average 60.5 years of age, predominantly male (95.0 %) and white (66.9 %), and had an average of 11.7 A1C tests during the study follow-up period. In high- and low-density urban communities, a one-unit higher LTPA facility density score was associated with 1 % and 3 % greater likelihood of in-range A1C tests during follow-up, respectively, but no association was observed among patients living in suburban/small town and rural communities. Across community types, closer park distance was not associated with subsequent greater odds of in-range A1C tests. Unexpectedly, in low-density urban areas, the likelihood of in-range A1C tests was 1 % lower at farther park distances. CONCLUSIONS:These results suggest that broader access to LTPA facilities, but not park proximity, may contribute in small ways to maintaining glycemic control after T2D diagnosis in urban communities. Tailored interventions may be needed to promote patients' effective use of LTPA facilities and parks.

OBJECTIVE:The objective of this study was to evaluate potential sources of heterogeneity in the effect of calorie labeling on fast-food purchases among restaurants located in areas with different neighborhood characteristics. METHODS:In a quasi-experimental design, using transaction data from 2329 Taco Bell restaurants across the United States between 2008 and 2014, we estimated the relationships of census tract-level income, racial and ethnic composition, and urbanicity with the impacts of calorie labeling on calories purchased per transaction. RESULTS:Calorie labeling led to small, absolute reductions in calories purchased across all population subgroups, ranging between -9.3 calories (95% CI: -18.7 to 0.0) and -37.6 calories (95% CI: -41.6 to -33.7) 2 years after labeling implementation. We observed the largest difference in the effect of calorie labeling between restaurants located in rural compared with those located in high-density urban census tracts 2 years after implementation, with the effect of calorie labeling being three times larger in urban areas. CONCLUSIONS:Fast-food calorie labeling led to small reductions in calories purchased across all population subgroups except for rural census tracts, with some subgroups experiencing a greater benefit.

BACKGROUND:Online ordering in food pantries may support food security among adults with low socioeconomic status. PURPOSE/OBJECTIVE:Determine the impact of a transition from in-person ordering to online ordering on the food security status of food pantry clients. METHODS:For this quasi-experimental study, we recruited participants from Met Council's Kosher Food Network in New York City, including one pantry in Staten Island (intervention) and three pantries in the Bronx, Queens, and Brooklyn (comparison). The final sample included 114 and 90 adults in the intervention and comparison groups, respectively, at baseline (April-July 2023); and 77 and 58 adults in those groups during follow-up (October-December 2023). Using a six-item survey, we assessed food security status, where scores range from zero to six points and higher points indicate lower food security. Secondary outcomes included nutrition security status, fruit and vegetable intake, and pantry wait time. We used a difference-in-differences approach to assess differences in outcomes between conditions, including testing for differences by age (18-64 vs. ≥65 years). RESULTS:Food security scores decreased in the intervention and comparison groups over time, with no difference in the decrease between groups (P = .87). Yet, among younger adults in the intervention group, wait time decreased during follow-up, and increased in the comparison group (difference-in-differences = -12.1 minutes (95% CI: -21.9, -2.4); P = .02). We did not observe similar differences among older adults (P = .83), nor significant changes in other outcomes. CONCLUSIONS:The transition to online ordering did not influence food security status among food pantry clients but may help to save time, especially among younger adults. CLINICAL TRIALS REGISTRATION/BACKGROUND:NCT05752721.

Prior studies assessing the impact of calorie labels in fast-food settings have relied on comparisons across local and state jurisdictions with and without labeling mandates; several well-designed studies indicate a small reduction of calories purchased as a result of the labels. This study exploits a staggered roll-out of calorie labels in California to study the same issue using a novel comparison of in-store purchases with calorie information and drive-through purchases without calorie information at the same locations. With this design, consumers in both the treatment and comparison groups have been subject to the same social signals associated with the policy change and may have been exposed to calorie information during prior purchases, narrowing the intervention under study to the impact of posted menu labels at the point of purchase. Transactions (N = 201,418,976) at 424 unique restaurants at a single fast-food chain were included and a difference-in-differences design was used to examine changes one and two years after the implementation of labels at in-store counters compared to baseline. Using this comparison of consumer purchases within the same jurisdictions, we found no meaningful impact of posted calorie labels at the point of purchase, suggesting that such labels did not induce behavioral change. Additional methods to strengthen the impact of labeling policies are worthy of further study.

Multi-site and multi-organizational teams are increasingly common in epidemiologic research; however, there is a lack of standards or best practices for achieving success in collaborative research networks in epidemiology. We summarize our experiences and lessons learned from the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a collaborative agreement between the Centers for Disease Control and Prevention and research teams at Drexel University, New York University, Johns Hopkins University and Geisinger, and the University of Alabama at Birmingham. We present a roadmap for success in collaborative epidemiologic research, with recommendations focused on the following areas to maximize efficiency and success in collaborative research agreements: 1) operational and administrative considerations; 2) data access and sharing of sensitive data; 3) aligning network research aims; 4) harmonization of methods and measures; and 5) dissemination of findings. Future collaborations can be informed by our experiences and ultimately dedicate more resources to achieving scientific aims and efficiently disseminating scientific work products.

Exposure to unhealthy food and beverage marketing is a major contributor to excessive weight gain among young people and it may disproportionately affect Black and Latinx communities. Appropriate and comprehensive regulations on food and beverage companies are essential, particularly as companies expand their reach and leverage the latest technologies to create marketing experiences using immersive virtual reality (VR). Although immersive VR technology is in its infancy, the potential effects of immersive VR food and beverage marketing on consumption, coupled with the history of racially targeted marketing by food and beverage corporations toward Black and Latinx communities, and the heightened burden of diet-related illnesses in Black and Latinx communities underscore a critical need to investigate immersive VR marketing targeting young people of color. This viewpoint will provide a brief description of VR food and beverage marketing as the newest food and beverage marketing frontier, highlight key concerns and knowledge gaps, and underscore future directions in research.