Faculty Bibliography

AIMS: To identify population characteristics associated with local variation in the prevalence of diabetic complications and compare the geographic distribution of different types of complications in New York City. METHODS: Using an all-payer database of emergency visits, we identified the proportion of unique adults with diabetes who also had cardiac, neurologic, renal and lower extremity complications. We performed multivariable regression to identify associations of demographic and socioeconomic factors, and diabetes-specific emergency department use with the prevalence of diabetic complications by Census tract. We also used geospatial analysis to compare local hotspots of diabetic complications. RESULTS: We identified 4.6million unique New York City adults, of which 10.5% had diabetes. Adjusting for demographic and socioeconomic factors, diabetes-specific emergency department use was associated with severe microvascular renal and lower extremity complications (p-values<0.001), but not with severe macrovascular cardiac or neurologic complications (p-values of 0.39 and 0.29). Our hotspot analysis demonstrated significant geographic heterogeneity in the prevalence of diabetic complications depending on the type of complication. Notably, the geographic distribution of hotspots of myocardial infarction were inversely correlated with hotspots of end-stage renal disease and lower extremity amputations (coefficients: -0.28 and -0.28). CONCLUSIONS: We found differences in the local geographic distribution of diabetic complications, which highlight the contrasting risk factors for developing macrovascular versus microvascular diabetic complications. Based on our analysis, we also found that high diabetes-specific emergency department use was correlated with poor diabetic outcomes. Emergency department utilization data can help identify the location of specific populations with poor glycemic control.

BACKGROUND: Few studies have used GPS data to analyze the relationship between Walk Score, transportation choice and walking. Additionally, the influence of Walk Score is understudied using trips rather than individuals as statistical units. The purpose of this study is to examine associations at the trip level between Walk Score, transportation mode choice, and walking among Paris adults who were tracked with GPS receivers and accelerometers in the RECORD GPS Study. METHODS: In the RECORD GPS Study, 227 participants were tracked during seven days with GPS receivers and accelerometers. Participants were also surveyed with a GPS-based web mapping application on their activities and transportation modes for all trips (6969 trips). Walk Score, which calculates neighborhood walkability, was assessed for each origin and destination of every trip. Multilevel logistic and linear regression analyses were conducted to estimate associations between Walk Score and walking in the trip or accelerometry-assessed number of steps for each trip, after adjustment for individual/neighborhood characteristics. RESULTS: The mean overall Walk Scores for trip origins were 87.1 (SD = 14.4) and for trip destinations 87.1 (SD = 14.5). In adjusted trip-level associations between Walk Score and walking only in the trip, we found that a walkable neighborhood in the trip origin and trip destination was associated with increased odds of walking in the trip assessed in the survey. The odds of only walking in the trip were 3.48 (95% CI: 2.73 to 4.44) times higher when the Walk Score for the trip origin was "Walker's Paradise" compared to less walkable neighborhoods (Very/Car-Dependent or Somewhat Walkable), with an identical independent effect of trip destination Walk Score on walking. The number of steps per 10 min (as assessed with accelerometry) was cumulatively higher for trips both originating and ending in walkable neighborhoods (i.e., "Very Walkable"). CONCLUSIONS: Walkable neighborhoods were associated with increases in walking among adults in Paris, as documented at the trip level. Creating walkable neighborhoods (through neighborhood design increased commercial activity) may increase walking trips and, therefore, could be a relevant health promotion strategy to increase physical activity.

A common policy approach to reducing childhood obesity aims to shape the environment in which children spend most of their time: neighborhoods and schools. This paper uses richly detailed data on the body mass index (BMI) of all New York City public school students in grades K-8 to assess the potential for place-based approaches to reduce child obesity. We document variation in the prevalence of obesity across NYC public schools and census tracts, and then estimate the extent to which this variation can be explained by differences in individual-level predictors (such as race and household income). Both unadjusted and adjusted variability across neighborhoods and schools suggest place-based policies have the potential to meaningfully reduce child obesity, but under most realistic scenarios the improvement would be modest.

BACKGROUND: Food and beverage marketing has been associated with childhood obesity. We quantified the number and type of food or beverage brands promoted by music celebrities, assessed the nutritional quality of the products, and examined Teen Choice Award data to assess the celebrities' popularity among adolescents. METHODS: This was a descriptive study. A list of music celebrities associated with the 2013 and 2014 Billboard Hot 100 Chart, which ranks songs according to sales and radio impressions, was compiled. Data on celebrity endorsements were gathered from official company Web sites, YouTube commercials, an advertising database, and media reports. Nutritional quality of foods was assessed according to the Nutrient Profile Index, whereas nonalcoholic beverages were evaluated based on calories from added sugar. Teen Choice Award nominations were used to measure the celebrities' popularity among adolescents. RESULTS: Of the 590 endorsements made by the 163 celebrities in the sample, consumer goods (eg, fragrances, makeup) represented the largest endorsement category (26%), followed by food and beverage (18%) and retail (11%). Sixty-five celebrities were collectively associated with 57 different food and beverage brands owned by 38 parent companies. Of these 65 celebrities, 53 (81.5%) had >/=1 Teen Choice Award nomination. Forty-nine (71%) of the 69 nonalcoholic beverage references promoted sugar-sweetened beverages. Twenty-one (80.8%) of the 26 endorsed foods were energy dense and nutrient poor. Baauer, will.i.am, Justin Timberlake, Maroon 5, and Britney Spears had the most food and beverage endorsements. CONCLUSIONS: This study demonstrates that music celebrities who are popular among adolescents endorse energy-dense, nutrient-poor products.

Previous research has highlighted the salience of spatial stigma on the lives of low-income residents, but has been theoretical in nature and/or has predominantly utilised qualitative methods with limited generalisability and ability to draw associations between spatial stigma and measured cardiovascular health outcomes. The primary objective of this study was to evaluate relationships between perceived spatial stigma, body mass index (BMI), and blood pressure among a sample of low-income housing residents in New York City (NYC). Data come from the community-based NYC Low-income Housing, Neighborhoods and Health Study. We completed a crosssectional analysis with survey data, which included the four items on spatial stigma, as well objectively measured BMI and blood pressure data (analytic n=116; 96.7% of the total sample). Global positioning systems (GPS) tracking of the sample was conducted for a week. In multivariable models (controlling for individual-level age, gender, race/ethnicity, education level, employment status, total household income, neighborhood percent non-Hispanic Black and neighborhood median household income) we found that participants who reported living in an area with a bad neighborhood reputation had higher BMI (B=4.2, 95%CI: -0.01, 8.3, P=0.051), as well as higher systolic blood pressure (B=13.2, 95%CI: 3.2, 23.1, P=0.01) and diastolic blood pressure (B=8.5, 95%CI: 2.8, 14.3, P=0.004). In addition, participants who reported living in an area with a bad neighborhood reputation had increased risk of obesity/overweight [relative risk (RR)=1.32, 95%CI: 1.1, 1.4, P=0.02) and hypertension/pre-hypertension (RR=1.66, 95%CI: 1.2, 2.4, P=0.007). However, we found no differences in spatial mobility (based GPS data) among participants who reported living in neighborhoods with and without spatial stigma (P>0.05). Further research is needed to investigate how placebased stigma may be associated with impaired cardiovascular health among individuals in stigmatised neighborhoods to inform effective cardiovascular risk reduction interventions.

BACKGROUND: This study used cross-sectional data to test the independent relationship of proximity to chain fast-food outlets and proximity to full-service supermarkets on the frequency of mealtime dining at fast-food outlets in two major urban areas, using three approaches to define access. Interactions between presence of a supermarket and presence of fast-food outlets as predictors of fast-food dining were also tested. METHODS: Residential intersections for respondents in point-of-purchase and random-digit-dial telephone surveys of adults in Philadelphia, PA, and Baltimore, MD, were geocoded. The count of fast-food outlets and supermarkets within quarter-mile, half-mile, and 1-mile street network buffers around each respondent's intersection was calculated, as well as distance to the nearest fast-food outlet and supermarket. These variables were regressed on weekly fast-food dining frequency to determine whether proximity to fast food and supermarkets had independent and joint effects on fast-food dining. RESULTS: The effect of access to supermarkets and chain fast-food outlets varied by study population. Among telephone survey respondents, supermarket access was the only significant predictor of fast-food dining frequency. Point-of-purchase respondents were generally unaffected by proximity to either supermarkets or fast-food outlets. However, >/=1 fast-food outlet within a 1-mile buffer was an independent predictor of consuming more fast-food meals among point-of-purchase respondents. At the quarter-mile distance, >/=1 supermarket was predictive of fewer fast-food meals. CONCLUSIONS: Supermarket access was associated with less fast-food dining among telephone respondents, whereas access to fast-food outlets were associated with more fast-food visits among survey respondents identified at point-of-purchase. This study adds to the existing literature on geographic determinants of fast-food dining behavior among urban adults in the general population and those who regularly consume fast food.