Faculty Bibliography

BACKGROUND:Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes. OBJECTIVE:This paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk. METHODS:The Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region. RESULTS:The Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement. CONCLUSIONS:The Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/21377.

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.

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.

INTRODUCTION/BACKGROUND:Previous research on sugar-sweetened beverage trends has focused on self-reported consumption from surveys. Few studies used objective store sales or explored differences by area-level demographics and store type. METHODS:The average volume of beverages sold per store per 3-digit zoning improvement plan code from 2006 to 2015 was calculated using national Nielsen Retail Scanner point-of-sale data from 24,240 stores. A multilevel regression model analyzed annual trends, with random intercepts for state and separate models for beverage type (regular soda, no/low-calorie soda, other sugary drinks, 100% fruit juice, bottled water). Differences by store type (convenience, supermarkets, drug stores, mass merchandisers) and area-level demographics (categorized as tertiles) were examined. Data were analyzed in 2019. RESULTS:The model-based estimates indicated that sales of regular soda (-11.8%), no/low-calorie soda (-19.8%), and 100% fruit juice (-31.9%) decreased over time, whereas sales of bottled water (+34.4%) increased and sales of other sugary drinks remained stable (+2.4%). Decreases in sugar-sweetened beverage sales were largely concentrated in supermarkets and larger in areas with high income and education levels and a high percentage of black and Hispanic people. There were also relatively larger increases in bottled water sales in states located in the South and Midwest. CONCLUSIONS:The finding that sales of sugar-sweetened beverages decreased over time, whereas sales of bottled water increased is encouraging because sugar-sweetened beverage consumption is linked to obesity and other chronic conditions. This study provides a novel, rigorous assessment of U.S. beverage sales trends and differences by community and store characteristics.

Using objectively-measured height and weight data from academic years 2009-2013 (n = 1,114,010 student-year observations), we estimated the association between the food outlet in closest proximity to schools and the likelihood of obesity among New York City public high school students. Obesity risk was higher for students with a corner store as the nearest option to schools, regardless of whether other food outlet types were located within a quarter mile or a half mile of schools (i.e., benchmarks for zoning policies). Policymakers may want to consider introducing healthier food options near schools, in conjunction with programs to support changes within corner stores.

OBJECTIVE:s rates of childhood obesity and pediatric type 2 diabetes (T2D) increase, a better understanding is needed of how these two conditions relate, and which subgroups of children are more likely to develop diabetes with and without obesity. METHODS:To compare hotspots of childhood obesity and pediatric T2D in New York City, we performed geospatial clustering analyses on obesity estimates obtained from surveys of school-aged children and diabetes estimates obtained from healthcare claims data, from 2009-2013. Analyses were performed at the Census tract level. We then used multivariable regression analysis to identify sociodemographic and environmental factors associated with these hotspots. RESULTS:We identified obesity hotspots in Census tracts with a higher proportion of Black or Hispanic residents, with low median household income, or located in a food swamp. 51.1% of pediatric T2D hotspots overlapped with obesity hotspots. For pediatric T2D, hotspots were identified in Census tracts with a higher proportion of Black residents and a lower proportion of Hispanic residents. CONCLUSIONS:Non-Hispanic Black neighborhoods had a higher probability of being hotspots of both childhood obesity and pediatric type 2 diabetes. However, we identified a discordance between hotspots of childhood obesity and pediatric diabetes in Hispanic neighborhoods, suggesting either under-detection or under-diagnosis of diabetes, or that obesity may influence diabetes risk differently in these two populations. These findings warrant further investigation of the relationship between childhood obesity and pediatric diabetes among different racial and ethnic groups, and may help guide pediatric public health interventions to specific neighborhoods.

OBJECTIVE:Conceptualisations of 'food deserts' (areas lacking healthful food/drink) and 'food swamps' (areas overwhelm by less-healthful fare) may be both inaccurate and incomplete. Our objective was to more accurately and completely characterise food/drink availability in urban areas. DESIGN/METHODS:Cross-sectional assessment of select healthful and less-healthful food/drink offerings from storefront businesses (stores, restaurants) and non-storefront businesses (street vendors). SETTING/METHODS:Two areas of New York City: the Bronx (higher-poverty, mostly minority) and the Upper East Side (UES; wealthier, predominantly white). PARTICIPANTS/METHODS:All businesses on 63 street segments in the Bronx (n 662) and on 46 street segments in the UES (n 330). RESULTS:Greater percentages of businesses offered any, any healthful, and only less-healthful food/drink in the Bronx (42·0 %, 37·5 %, 4·4 %, respectively) than in the UES (30 %, 27·9 %, 2·1 %, respectively). Differences were driven mostly by businesses (e.g. newsstands, gyms, laundromats) not primarily focused on selling food/drink - 'other storefront businesses' (OSBs). OSBs accounted for 36·0 % of all food/drink-offering businesses in the Bronx (more numerous than restaurants or so-called 'food stores') and 18·2 % in the UES (more numerous than 'food stores'). Differences also related to street vendors in both the Bronx and the UES. If street vendors and OSBs were not captured, the missed percentages of street segments offering food/drink would be 14·5 % in the Bronx and 21·9 % in the UES. CONCLUSIONS:Of businesses offering food/drink in communities, OSBs and street vendors can represent substantial percentages. Focusing on only 'food stores' and restaurants may miss or mischaracterise 'food deserts', 'food swamps', and food/drink-source disparities between communities.

Using data from the United States Behavioral Risk Factor Surveillance System (2003-2012; N = 3,397,124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations.

No studies have documented the prevalence of the food industry's funding of academic programs, which is problematic because such funding can create conflicts of interest in research and clinical practice. We aimed to quantify the publicly available information on the food industry's donations to academic programs by documenting the amount of donations given over time, categorizing the types of academic programs that receive food industry donations, cataloguing the source of the donation information, and identifying any stated reasons for donations. Researchers cataloged online data from publicly available sources (e.g., official press releases, news articles, tax documents) on the food industry's donations to academic programs from 2000 to 2016. Companies included 26 food and beverage corporations from the 2016 Fortune 500 list in the United States. Researchers recorded the: (1) monetary value of the donations; (2) years the donations were distributed; (3) the name and type of recipient; (4) source of donation information; and (5) reasons for donations. Adjusting for inflation, we identified $366 million in food industry donations (N = 3274) to academic programs. Universities received 45.2% (n = 1480) of donations but accounted for 67.9% of total dollars given in the sample. Community colleges, schools (i.e., preschool, elementary, middle, and high schools), and academic nonprofits, institutes, foundations, and research hospitals collectively received 54.8% of the donations, but made up less than one-third of the monetary value of donations. Half of the donations (49.0%) did not include a stated reason for the donation. In our sample, donations grew from $3 million in 2000 to $24 million in 2016. Food companies in our sample donated millions of dollars to universities and other academic programs but disclosed little information on the purpose of the donations. Achieving transparency in donation practices may only be possible if federal policies begin to require disclosures or if companies voluntarily disclose information.

This study used interviews with New York City Hispanic Caribbean (HC) restaurant owners, managers, and cooks/chefs (n=19) to examine perceptions concerning the healthfulness of the HC diet and diet-related disparities in the HC community, and document factors potentially influencing their engagement in community nutrition interventions. The interviews revealed high awareness of diet-related issues. Respondents had mixed notions concerning their role in improving community food environments, noting important barriers for collaboration to consider in future interventions. The study underscores the important role of ethnic restaurants, providing information to facilitate engagement with this largely untapped sector in immigrant/ethnic communities in the US.