Faculty Bibliography

BACKGROUND/UNASSIGNED:Leisure-time physical activity (LTPA) is a well-established contributor to physical, psychological, and social well-being worldwide. Human touch also plays a vital role in life course health, yet opportunities for safe, consensual touch are often limited, particularly in LTPA settings. For gay, bisexual, transgender, and queer (GBTQ) men, barriers to affirming LTPA spaces can make it particularly difficult to access such benefits. In response, community-based approaches that integrate touch are needed, alongside systematic evaluations of such strategies. "The Studio" (pseudonym), a membership-based wellness community, addresses this gap by offering touch-centered partner yoga and bodywork programs designed to support the holistic health of GBTQ men. OBJECTIVE/UNASSIGNED:This protocol describes a mixed methods evaluation of the Studio's touch-based yoga programming in New York City. The primary aim is to assess the feasibility and acceptability of implementing a touch-centered partner yoga program within a GBTQ community wellness setting. Secondary aims include exploring preliminary physical, emotional, and social outcomes associated with participation, including flexibility, stress, body awareness, social connection, trust, and belonging. METHODS/UNASSIGNED:The evaluation uses a pre- and posttest mixed methods design. A total of 40-50 participants will be recruited from new Studio members. Quantitative measures will include flexibility (sit-and-reach and goniometry), stress (Perceived Stress Scale), body awareness (Multidimensional Assessment of Interoceptive Awareness), and resilience (Brief Resilience Scale). Social network analysis will map participant connections before and after program participation. Qualitative data will be collected through semistructured interviews with 15-20 participants, or until saturation is reached, focusing on comfort with touch, emotional regulation, and experiences of community connectedness. Survey and interview guides will be codeveloped with a community advisory group to ensure cultural responsiveness and relevance. Findings will be integrated using triangulation methods to explore convergence across data sources. RESULTS/UNASSIGNED:As of March 2026, this study has not yet begun. Institutional Review Board submission is planned for September 2026. Afterward, study instruments will be finalized and pilot-tested with Studio teachers. Participant recruitment is projected to begin in July 2027, and data collection will include 3 time points (baseline, postintervention, and 4-6 wk follow-up). Data analysis and dissemination of findings are expected in 2028. Preliminary pilot testing of the survey instruments with Studio employees and community advisory group members will indicate feasibility and cultural fit. CONCLUSIONS/UNASSIGNED:This evaluation will be among the first to systematically examine touch-focused partner yoga for GBTQ men in a community wellness setting. Findings are expected to provide novel insights into the feasibility and the role of intentional touch in LTPA spaces, support trauma-informed and inclusive wellness practices, and contribute to broader discourse on GBTQ health promotion and intervention. Results will be disseminated to the Studio employees, members, and GBTQ-focused wellness organizations, as well as through peer-reviewed publications and conferences.

BACKGROUND:Sugary drink taxes have been implemented in several U.S. jurisdictions, but we know little about the impact of taxes on calories purchased in restaurants. The impact may differ in restaurant (vs. non-restaurant) settings because restaurant consumers may be less likely to travel to other jurisdictions for a single meal, choose no beverage or non-taxed beverages, decrease their beverage size, or order combo meals where the drink is bundled with other items at a single price. METHODS AND FINDINGS/RESULTS:We used six years of transaction-level sales data (2015-2020) from 7,341 Taco Bell restaurant locations to estimate the association of sugary drink policies with beverage calories purchased in the drive-through setting of fast food restaurants over time. Taco Bell restaurants represents a large sample size of data from several U.S. jurisdictions across a long follow-up period, which is unique in the literature. We defined the treatment group as restaurants in five jurisdictions where taxes were ever implemented (Albany, CA; Cook County, IL; Oakland, CA; Philadelphia, PA; Seattle, WA) (n = 60 restaurants). We identified a group of comparison restaurants where taxes were never implemented using synthetic control methods (n = 60 restaurants). We used a difference-in-differences design with calendar month and restaurant fixed effects to compare changes in outcomes between groups between the baseline (3-14 months prior to tax implementation) and 3- to 24-month follow-up periods, overall and by jurisdiction. Our primary outcome measure was beverage calories per transaction, from individually-purchased beverages and combo meals (separately). In the baseline period, average beverage calories per transaction were 51.1 (SD = 8.6) in the tax group and 42.3 (SD = 7.4) in the comparison group; and 119.5 (SD = 15.3) and 115.0 (SD = 23.0) beverage calories per transaction in combo meals. Overall, we observed no association between taxes and changes in beverage calories per transaction between groups during the follow-up period, including from individual beverage items (difference-in-differences = -0.3 (95% CI [-0.8, 1.2]) and combo meals (difference-in-differences = -4.3 (95% CI [-13.5, 5.0]). We observed similar results by location, except in Oakland, CA, where customers purchased 16.8 (95% CI 19.6, 14.1) fewer beverage calories per transaction from combo meals; the association was null after conditioning on the purchase of a beverage (difference-in-differences = -1.01 [-4.93, 2.92)]). The main limitations of our study methodology include the exclusion of beverage calorie data from in-store transactions and that the majority of the restaurants in our sample were located in Cook County. CONCLUSIONS:Though we observed differences in certain jurisdictions, overall our findings suggest that sugary drink taxes may not be effective in reducing beverage calorie consumption in fast food restaurants.

INTRODUCTION/UNASSIGNED:This study leverages advertising industry data to quantify social media advertising expenditures and advertising impressions of the food and beverage industry on Facebook, Twitter/X, and Instagram from January 2019 to August 2021. METHODS/UNASSIGNED:=18 months). Primary outcomes were monthly trends expenditures of food/beverage advertising and the number of views and expenditures of food/beverage advertising by platform (e.g., TV, online, mobile, print). Primary outcomes was measured by monthly expenditures by (1) social media company, (2) brand, and (3) before COVID-19 versus the first year of the pandemic. RESULTS/UNASSIGNED:for interaction<0.001). CONCLUSIONS/UNASSIGNED:These data reveal that the food/beverage industry spends at least $2.8 billion on social media advertising, which generate billions of views for their products online. Determining adults' exposure to social media food advertising is critical for understanding the upstream factors that shape the risk for diet-related diseases.

OBJECTIVE:To determine the feasibility of an online grocery pilot aimed at supporting healthy food purchases for caregivers of individuals with low income. METHODS:A pretest-posttest pilot study was conducted among 59 primary household food shopper caregivers living ≤ 130% of the poverty line. The 8-week randomized pilot had 4 groups: (1) free delivery-only, (2) trust-targeting SMS, (3) matching credit for online healthy purchases, and (4) grocery list recommendations. The groups received the program concomitantly from October to December, 2022. Feasibility was assessed through the setup of an online grocery account and receipt of the intervention materials via text. Acceptability was assessed via postintervention interviews and participants' ratings of the intervention. RESULTS:Feasibility was medium-high: 47% created an online grocery account, 61% watched the program tutorial. Acceptability was high: 90% found the tutorial helpful, all received text messages, 82% deemed them useful. CONCLUSIONS AND IMPLICATIONS/CONCLUSIONS:The promising feasibility and acceptability suggest a potential for a fully powered trial behavioral intervention to support online healthy food shopping.

INTRODUCTION/BACKGROUND:Menu labels were federally mandated in May 2018, but the authors are not aware of any work that has evaluated the impact of the national rollout of this legislation in restaurants using a comparison group to account for potential bias. METHODS:Using synthetic control methods, Taco Bell restaurants that implemented menu labels after nationwide labeling (n=5,060 restaurants) were matched to restaurants that added calorie labels to menus after local labeling legislation (and prior to nationwide labeling). The effect of menu labeling on calories purchased per transaction after nationwide labeling between groups (i.e., "later-treated" and "early-treated" restaurants) was estimated using a two-way fixed effects regression model, with time modeled as relative month from implementation and fixed effects for calendar month and restaurant. RESULTS:In the baseline period, average calories per transaction was 1,242 (SD=178) in the national menu labeling group and 1,245 (SD=183.9) in the comparison group, with parallel trends between groups. Difference-in-differences model results indicated that transactions from restaurants in the national menu labeling group included 7.4 (95% CI: 7.3, 7.5) more calories than was predicted based on the trend in the comparison group. Average number of total transactions per month decreased ∼2% more in the national menu labeling group relative to the comparison group. CONCLUSIONS:Negligible changes were observed in calories purchased and number of transactions in restaurants that added calorie labels due to national legislation, above and beyond secular changes. Other strategies may be necessary to promote meaningful decreases in daily calories purchased in restaurants going forward.

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.

BACKGROUND:Nudges offer a promising tool to reduce sugary drink intake among children who are most at risk for diet-related disease. OBJECTIVE:To examine the impact of online store nudges on purchases of sugary drinks for children in lower-income households. METHODS:Caregivers with lower-income were recruited to an online shopping experiment and instructed to spend $10-$30 on three beverages for their child aged 1-5 years. Participants were randomized to navigate an online supermarket in its standard version (n = 1106) or a version with nudges (n = 1135), including a product placement nudge (i.e. placing healthy beverages in prominent positions) and a swap nudge (i.e. offering a swap of water, plain milk and/or 100% fruit juice upon selection of sugary drinks). RESULTS:On average, participants purchased 1887 (SD = 2113) and 620 (SD = 1528) calories from sugary drinks per basket in the control and experimental conditions, respectively. Model-based results indicate that those in the experimental condition purchased 1267 (95% CI: 1419, 1114) fewer calories from sugary drinks, and fewer grams of total sugar (β = -253.5 g (95% CI: -286.3, -220.6)) and added sugar (β = -287.8 g (95% CI: -323.1, -252.5)) purchased from sugary drinks. CONCLUSION/CONCLUSIONS:Nudges may be an effective, acceptable, scalable strategy for leading caregivers in lower-income households to purchase fewer sugary drinks for their children.

OBJECTIVE:The aim of this study was to examine relationships between the food environment and obesity by community type. METHODS:Using electronic health record data from the US Veterans Administration Diabetes Risk (VADR) cohort, we examined associations between the percentage of supermarkets and fast-food restaurants with obesity prevalence from 2008 to 2018. We constructed multivariable logistic regression models with random effects and interaction terms for year and food environment variables. We stratified models by community type. RESULTS:Mean age at baseline was 59.8 (SD = 16.1) years; 93.3% identified as men; and 2,102,542 (41.8%) were classified as having obesity. The association between the percentage of fast-food restaurants and obesity was positive in high-density urban areas (odds ratio [OR] = 1.033; 95% CI: 1.028-1.037), with no interaction by time (p = 0.83). The interaction with year was significant in other community types (p < 0.001), with increasing odds of obesity in each follow-up year. The associations between the percentage of supermarkets and obesity were null in high-density and low-density urban areas and positive in suburban (OR = 1.033; 95% CI: 1.027-1.039) and rural (OR = 1.007; 95% CI: 1.002-1.012) areas, with no interactions by time. CONCLUSIONS:Many healthy eating policies have been passed in urban areas; our results suggest such policies might also mitigate obesity risk in nonurban areas.