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.

Objective/UNASSIGNED:To adapt and apply the Nutrition Environment Measures Survey for Restaurants (NEMS-R) to Hispanic Caribbean (HC) restaurants and examine associations between restaurant characteristics and nutrition environment measures. Methods/UNASSIGNED:We adapted the NEMS-R for HC cuisines (Cuban, Puerto Rican, Dominican) and cardiovascular health-promoting factors, and applied the instrument (NEMS-HCR) to a random sample of HC restaurants in New York City (NYC) (N=89). Multivariable linear regression was used to assess independent associations between NEMS-HCR score and restaurant characteristics (cuisine, size, type [counter-style vs sit-down] and price). Results/UNASSIGNED:None of the menus in the restaurants studied listed any main dishes as "healthy" or "light." More than half (52%) offered mostly (>75%) nonfried main dishes, and 76% offered at least one vegetarian option. The most common facilitator to healthy eating was offering reduced portion sizes (21%) and the most common barrier was having salt shakers on tables (40%). NEMS-HCR scores (100-point scale) ranged from 24.1-55.2 (mean=39.7). In multivariable analyses, scores were significantly related to cuisine (with Puerto Rican cuisine scoring lower than Cuban and Dominican cuisines), and size (with small [<22 seats] restaurants scoring lower than larger restaurants). We found a significant quadratic association with midpoint price, suggesting that scores increased with increasing price in the lowest price range, did not vary in the middle range, and decreased with increasing price in the highest range. Conclusions/UNASSIGNED:Our application of the NEMS-R to HC restaurants in NYC revealed areas for potential future interventions to improve food offerings and environmental cues to encourage healthful choices.

Background: Household food purchasing behavior has gained interest as an intervention to improve nutrition and nutrition-associated outcomes. However, evaluating food expenditures is challenging in epidemiological studies. Assessment methods that are both valid and feasible for use among diverse, low-income populations are needed. We therefore developed a novel simple annotated receipt method to assess household food purchasing. First, we describe and evaluate the extent to which the method captures food purchasing information. We then evaluate within- and between-household variation in weekly food purchasing to determine sample sizes and the number of weeks of data needed to measure household food purchasing with adequate precision. Methods: Four weeks of food purchase receipt data were collected from 260 low-income households in the Minneapolis-St. Paul metropolitan area. The proportion of receipt line items that could not be coded into one of 11 food categories (unidentified) was calculated, and a zero-inflated negative binomial regression was used to evaluate the association between unidentified receipt items and participant characteristics and store type. Within- and between-household coefficients of variation were calculated for total food expenditures and several food categories. Results: A low proportion of receipt line items (1.6%) could not be coded into a food category and the incidence of unidentified items did not appreciably vary by participant characteristics. Weekly expenditures on foods high in added sugar had higher within- and between-household coefficients of variation than weekly fruit and vegetable expenditures. To estimate mean weekly food expenditures within 20% of the group's usual ("true") expenditures, 72 households were required. Nine weeks of data were required to achieve an r = 0.90 between observed and usual weekly food expenditures. Conclusions: The simple annotated receipt method may be a feasible tool for use in assessing food expenditures of low-income, diverse populations. Within- and between-household coefficients of variation suggest that the number of weeks of data or group sizes required to precisely estimate usual household expenditures is higher for foods high in added sugar compared to fruits and vegetables.

Prior research has documented the ways in which financial hardships negatively impact health, particularly mental health. However, this association between financial hardships and mental health outcomes has rarely been examined in sexual minorities. The purpose of this study was to examine associations between financial hardships and mental health burdens among a sample of gay, bisexual and other men who have sex with men (MSM) in Paris, France. Participants (n = 580) completed a cross-sectional survey advertised on a geosocial networking application. Participants responded to measures of mental health, financial hardship, and socio-demographics. Modified Poisson models were used to estimate risk ratios (RRs) and 95% confidence intervals (CI) for the associations between financial hardship and the following outcomes: 1) depressive symptoms, 2) anxiety symptoms, and 3) psychological distress. After adjusting for socio-demographics, high financial hardships were associated with depressive symptoms (aRR: 1.48, 95% CI: 1.04, 2.11) and psychological distress (aRR: 1.56, 95% CI: 1.09, 2.23). Analyses also demonstrated that stress acts as a mediating variable. These preliminary results suggest that future interventions to reduce financial hardships may have positive effects on the mental health of such a population.

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.

BACKGROUND:Tobacco remains the leading cause of preventable death in the United States, with 41,000 deaths attributable to secondhand smoke (SHS) exposure. On July 30, 2018, the U.S. Department of Housing and Urban Development passed a rule requiring public housing authorities to implement smoke-free housing (SFH) policies. OBJECTIVES/OBJECTIVE:Prior to SFH policy implementation, we measured self-reported and objective SHS incursions in a purposeful sample of 21 high-rise buildings (>15 floors) in New York City (NYC): 10 public housing and 11 private sector buildings where most residents receive federal housing subsidies (herein 'Section 8' buildings). METHODS:) from low-cost particle monitors. SHS was measured for 7-days in non-smoking households (NYCHA n = 157, Section 8 n = 118 households) and in building common areas (n = 91 hallways and stairwells). RESULTS:was observed between and within buildings; on average nicotine concentrations were higher in NYCHA apartments and hallways than in Section 8 buildings (p < 0.05), and NYCHA residents reported seeing smokers in common areas more frequently. CONCLUSIONS:SFH policies may help in successfully reducing SHS exposure in public housing, but widespread pre-policy incursions suggest achieving SFH will be challenging.

OBJECTIVE/UNASSIGNED:To assess the accuracy of government inspection records, relative to ground observation, for identifying businesses offering foods/drinks. DESIGN/UNASSIGNED:Agreement between city and state inspection records v. ground observations at two levels: businesses and street segments. Agreement could be 'strict' (by business name, e.g. 'Rizzo's') or 'lenient' (by business type, e.g. 'pizzeria'); using sensitivity and positive predictive value (PPV) for businesses and using sensitivity, PPV, specificity and negative predictive value (NPV) for street segments. SETTING/UNASSIGNED:The Bronx and the Upper East Side (UES), New York City, USA. PARTICIPANTS/UNASSIGNED:All food/drink-offering businesses on sampled street segments (n 154 in the Bronx, n 51 in the UES). RESULTS/UNASSIGNED:By 'strict' criteria, sensitivity and PPV of government records for food/drink-offering businesses were 0·37 and 0·57 in the Bronx; 0·58 and 0·60 in the UES. 'Lenient' values were 0·40 and 0·62 in the Bronx; 0·60 and 0·62 in the UES. Sensitivity, PPV, specificity and NPV of government records for street segments having food/drink-offering businesses were 0·66, 0·73, 0·84 and 0·79 in the Bronx; 0·79, 0·92, 0·67, and 0·40 in the UES. In both areas, agreement varied by business category: restaurants; 'food stores'; and government-recognized other storefront businesses ('gov. OSB', i.e. dollar stores, gas stations, pharmacies). Additional business categories - 'other OSB' (barbers, laundromats, newsstands, etc.) and street vendors - were absent from government records; together, they represented 28·4 % of all food/drink-offering businesses in the Bronx, 22·2 % in the UES ('other OSB' and street vendors were sources of both healthful and less-healthful foods/drinks in both areas). CONCLUSIONS/UNASSIGNED:Government records frequently miss or misrepresent businesses offering foods/drinks, suggesting caveats for food-environment assessments using such records.

BACKGROUND:Tobacco remains a leading cause of preventable death in the U.S., responsible for more than 440,000 deaths each year. Approximately 10% of these deaths are attributable to exposure of non-smokers to secondhand smoke (SHS). Residents living in public multi-unit housing (MUH) are at excess risk for SHS exposure compared to the general population. On November 30, 2016, the U.S. Department of Housing and Urban Development (HUD) passed a rule requiring all public housing agencies to implement smoke-free housing (SFH) policies in their housing developments by July 30, 2018. METHODS:As part of a larger natural experiment study, we designed a protocol to evaluate indoor SHS levels before and after policy implementation through collection of repeat indoor air samples in non-smoking apartments and common areas of select high-rise NYCHA buildings subject to the HUD SFH rule, and also from socio-demographically matched private-sector high-rise control buildings not subject to the rule. A baseline telephone survey was conducted in all selected buildings to facilitate rapid recruitment into the longitudinal study and assess smoking prevalence, behaviors, and attitudes regarding the SFH policy prior to implementation. Data collection began in early 2018 and will continue through 2021. DISCUSSION/CONCLUSIONS:The baseline survey was completed by 559 NYCHA residents and 471 comparison building residents (response rates, 35, and 32%, respectively). Smoking prevalence was comparable between study arms (15.7% among NYCHA residents and 15.2% among comparison residents). The majority of residents reported supporting a building-wide smoke-free policy (63.0 and 59.9%, respectively). We enrolled 157 NYCHA and 118 comparison non-smoking households into the longitudinal air monitoring study and performed air monitoring in common areas. Follow up surveys and air monitoring in participant households occur every 6 months for 2.5 years. Capitalizing on the opportunity of this federal policy rollout, the large and diverse public housing population in NYC, and robust municipal data sources, this study offers a unique opportunity to evaluate the policy's direct impacts on SHS exposure. Methods in this protocol can inform similar SFH policy evaluations elsewhere.

INTRODUCTION/BACKGROUND:The present study measures how racially-targeted food and beverage ads affect adolescents' attitudes toward ads and brands, purchase intentions for advertised products, and willingness to engage with brands on social media. METHODS:Black and White adolescents were recruited through Survey Sampling International in 2016. Participants completed an online survey in which they were randomized to view either four food and beverage ads (e.g., soda, candy commercials) featuring Black actors or four food and beverage ads featuring White actors. RESULTS:For the two components of the attitudinal outcome, Black participants were more likely to report a positive affective response toward racially-similar ads compared to Whites. However, White participants were more likely to like ads that were racially-dissimilar compared to Black participants. Data were analyzed in 2016-2017, and we used an alpha level of 0.05 to denote statistical significance. CONCLUSIONS:Both Black and White adolescents reported more positive affective responses to ads that featured Blacks compared to ads that featured Whites. Because there were no differences on two outcomes, future research should examine the influence of racially-targeted marketing in real-world contexts (e.g., social media) and longitudinal exposure to targeted advertising on dietary behavior.