Faculty Bibliography

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.

We examine the causal link between proximity to fast food and the incidence of childhood obesity among low-income households in New York City. Using individual-level longitudinal data on students living in public housing linked to restaurant location data, we exploit the naturally occurring within-development variation in distance to fast food restaurants to estimate the impact of proximity on obesity. Since the assignment of households to specific buildings is based upon availability at the time of assignment to public housing, the distance between student residence and retail outlets-including fast food restaurants, wait-service restaurants, supermarkets, and corner stores-is plausibly random. Our credibly causal estimates suggest that childhood obesity increases with proximity to fast food, with larger effects for younger children who attend neighborhood schools.

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.

Background: The Veterans Administration (VA) cares for over 8 million U.S. veterans annually, approximately 20% of whom have prevalent diabetes. To foster research and intervention opportunities, we developed the VA Diabetes Risk (VADR) Cohort using the VA electronic health record, a national cohort of diabetes-free U.S. veterans receiving primary care at the VA since January 1, 2008. This cohort provides important opportunities to study community-level risk factors for diabetes, such as attributes of the food environment, via geospatial linkage to residence information. We describe here the cohort profile and diabetes incidence by sub-group.
Method(s): To be eligible, diabetes-free patients had to have at least 2 primary care visits at least 30 days apart prior to enrollment. Diabetes incidence was defined as having >=2 inpatient or outpatient encounters with diabetes ICD-9/10 codes, any prescription of diabetes medicine, or one encounter with diabetes ICD-9/10 codes and >=2 hemoglobin A1C >=6.5%. The incidence of diabetes was calculated as the number of new cases diagnosed per 1000 person-years (PY) through December 31, 2018. Demographic and comorbidities data were abstracted using diagnostic codes, labs, prescriptions, and vital signs.
Result(s): The VADR cohort consisted of 6.17 million veterans, the majority of whom were male (91.7%) and non- Hispanic (NH) white (75.7%). Nearly half were above 60 years of age at enrollment (48.8%). The diabetes incidence rate was 27.0 per 1000 PY, increasing with age from 13.3 per 1000 PY among adults <45 years old to 41.8 per 1000 PY among those 65 years and older. Incidence was higher among men than women (34.6 vs. 18.6 per 1000 PY) and higher among NH black patients compared to NH white patients (38 vs. 31.7 per 1000 PY).
Conclusion(s): The VADR cohort provides a novel infrastructure for examination of community-level risk factors for diabetes among veterans, and facilitates assessment of the impact of national or regional strategies to prevent or manage diabetes in veterans

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.

OBJECTIVE:This study aimed to examine the relationship between proximity to healthy and unhealthy food outlets around children's homes and their weight outcomes. METHODS:A total of 3,507,542 student-year observations of height and weight data from the 2009-2013 annual FitnessGram assessment of New York City public school students were used. BMI z scores were calculated, student obesity or obesity/overweight was determined using Centers for Disease Control and Prevention growth charts, and these data were combined with the locations of four food outlet types (fast-food restaurants, wait-service restaurants, corner stores, and supermarkets) to calculate distance to the nearest outlet. Associations between weight status outcomes and distance to these food outlet types were examined using neighborhood (census tract) fixed effects. RESULTS:Living farther than 0.025 mile (about half of a city block) from the nearest fast-food restaurant was associated with lower obesity and obesity/overweight risk and lower BMI z scores. Results ranged from 2.5% to 4.4% decreased obesity. Beyond this distance, there were generally no impacts of the food environment and little to no impact of other food outlet types. CONCLUSIONS:Proximity to fast-food restaurants was inversely related to childhood obesity, but no relationships beyond that were seen. These findings can help better inform policies focused on food access, which could, in turn, reduce childhood obesity.