Faculty Bibliography

Previous studies have identified an association between socioeconomic status and sleep health. While some research has studied this association among sexual minority groups, including men who have sex with men (MSM), they exclusively focused on US-based populations. The interplay between the two in shaping sleep health has not been previously examined on populations residing outside the US. This study considers both determinants, by investigating whether financial hardship is associated with sleep health among a sample of MSM in Paris, France. Broadcast advertisements were placed on a popular geosocial-networking smartphone application for MSM to direct users in Paris to a web-based survey measuring financial hardship and five dimensions of sleep health as well as socio-demographic characteristics. Modified Poisson models with robust error variance were computed to estimate risk ratios (RRs) and 95% confidence intervals (CI) for the associations between financial hardship and the following self-reported outcomes: 1) poor sleep quality, 2) short sleep duration; and 3) sleep problems. In total, 580 respondents completed the survey. In this sample, both financial hardship and poor sleep health were common - 45.5% reported that it was extremely, very, or somewhat difficult for them to meet their monthly payments on bills (referred to as "high financial hardship") and 30.1% rated their sleep as fairly bad or very bad (referred to as "poor sleep quality"). Multivariate models revealed that, compared to participants who reported low financial hardship, those who reported high financial hardship were more likely to report poor sleep quality (aRR: 1.35, 95% CI: 1.04, 1.77), to report problems falling asleep (aRR: 1.23, 95% CI: 1.02, 1.49), and to report problems staying awake in the daytime (aRR: 3.12, 95% CI: 1.83, 5.31). Future research should investigate whether this relationship is causal and determine whether interventions to reduce financial hardships could promote sleep health among MSM.

OBJECTIVES: This study aimed to evaluate the acceptability of smartphone-based text message- and voice-based ecological momentary assessment (EMA) methods among a sample of low-income housing residents in New York City. Using data from the community-based NYC Low Income Housing, Neighborhoods and Health Study (n = 112), the acceptability of text message- and voice-based EMA methods were assessed via survey. RESULTS: Overall, 88.4% of participants reported that they would participate in a study that utilized text message-based EMA. These analyses showed no appreciable differences by sub-groups (p > .05). Overall, 80.2% of participants reported that they would participate in a study that used voice-based EMA. This voice-based method was least acceptable among participants younger than 25 years old compared to participants of all other ages, chi2(2) = 10.107, p = .006 (among the younger participants 60.7% reported "yes" regarding the anticipated acceptability of voice-based EMA and 39.3% reported "no"). Overall, this work suggests that text message- and voice-based EMA methods are acceptable for use among low-income housing residents. However, the association between age and the acceptability of voice-based EMA suggests that these methods may be less suited for younger populations.

Little is known about how neighborhood noise influences cardiovascular disease (CVD) risk among low-income populations. The aim of this study was to investigate associations between neighborhood noise complaints and body mass index (BMI) and blood pressure (BP) among low-income housing residents in New York City (NYC), including the use of global positioning system (GPS) data. Data came from the NYC Low-Income Housing, Neighborhoods and Health Study in 2014, including objectively measured BMI and BP data (N = 102, Black = 69%), and 1 week of GPS data. Noise reports from "NYC 311" were used to create a noise complaints density (unit: 1000 reports/km2) around participants' home and GPS-defined activity space neighborhoods. In fully-adjusted models, we examined associations of noise complaints density with BMI (kg/m2), and systolic and diastolic BP (mmHg), controlling for individual- and neighborhood-level socio-demographics. We found inverse relationships between home noise density and BMI (B = -2.7 [kg/m2], p = 0.009), and systolic BP (B = -5.3 mmHg, p = 0.008) in the fully-adjusted models, and diastolic BP (B = -3.9 mmHg, p = 0.013) in age-adjusted models. Using GPS-defined activity space neighborhoods, we observed inverse associations between noise density and systolic BP (B = -10.3 mmHg, p = 0.019) in fully-adjusted models and diastolic BP (B = -7.5 mmHg, p = 0.016) in age-adjusted model, but not with BMI. The inverse associations between neighborhood noise and CVD risk factors were unexpected. Further investigation is needed to determine if these results are affected by unobserved confounding (e.g., variations in walkability). Examining how noise could be related to CVD risk could inform effective neighborhood intervention programs for CVD risk reduction.

INTRODUCTION: Residents of some low-income neighborhoods have limited access to fresh fruits and vegetables. In 2008, New York City issued new mobile fruit and vegetable cart licenses for neighborhoods with inadequate availability of fresh produce. Some of these carts were equipped with electronic benefit transfer (EBT) machines, allowing them to accept Supplemental Nutrition Assistance Program (SNAP) benefits. This article examines the association between type and quantities of fruits and vegetables purchased from mobile fruit and vegetable vendors and consumer characteristics, including payment method. METHODS: Customers at 4 produce carts in the Bronx, New York, were surveyed during 3 periods in 2013 and 2014. Survey data, including purchased fruit and vegetable quantities, were analyzed using multivariable negative binomial regressions, with payment method (cash only vs EBT or EBT and cash) as the primary independent variable. Covariates included availability of EBT, vendor, and customer sociodemographic characteristics. RESULTS: A total of 779 adults participated in this study. Shoppers who used SNAP benefits purchased an average of 5.4 more cup equivalents of fruits and vegetables than did shoppers who paid with cash. Approximately 80% of this difference was due to higher quantities of purchased fruits. CONCLUSION: Expanding access to EBT machines at mobile produce carts may increase purchases of fruits and vegetables from these vendors.

BACKGROUND:This research evaluated the effects of financial incentives and purchase restrictions on food purchasing in a food benefit program for low income people. METHODS:Participants (n=279) were randomized to groups: 1) Incentive- 30% financial incentive for fruits and vegetables purchased with food benefits; 2) Restriction- no purchase of sugar-sweetened beverages, sweet baked goods, or candies with food benefits; 3) Incentive plus Restriction; or 4) Control- no incentive or restrictions. Participants received a study-specific debit card where funds were added monthly for 12-weeks. Food purchase receipts were collected over 16 weeks. Total dollars spent on grocery purchases and by targeted food categories were computed from receipts. Group differences were examined using general linear models. RESULTS:Weekly purchases of fruit significantly increased in the Incentive plus Restriction ($4.8) compared to the Restriction ($1.7) and Control ($2.1) groups (p <.01). Sugar-sweetened beverage purchases significantly decreased in the Incentive plus Restriction (-$0.8 per week) and Restriction ($-1.4 per week) groups compared to the Control group (+$1.5; p< .0001). Sweet baked goods purchases significantly decreased in the Restriction (-$0.70 per week) compared to the Control group (+$0.82 per week; p < .01). CONCLUSIONS:Paired financial incentives and restrictions on foods and beverages purchased with food program funds may support more healthful food purchases compared to no incentives or restrictions. CLINICAL TRIAL REGISTRATION:Clinicaltrials.gov Identifier: NCT02643576 .

By mid-2018, federal policy will require chain restaurants with more than 20 U.S. locations to include calorie information on their menus. Despite high expectations that this policy would encourage healthier eating, most studies of local policies to mandate calorie labels have demonstrated little impact on consumer choice. In this article, the authors adapt Burton and Kees's (2012) conceptual framework for eating behavior change to better understand the limited impact of these policies thus far. Using two surveys of fast-food consumers in Philadelphia, the authors estimate the percentage who might reasonably be expected to respond to calorie labels given the requirements of the Burton and Kees model. They find that as few as 8% of fast-food consumers meet all the model's requirements and, therefore, would be expected to change their eating behavior as a result of calorie information. The authors use the model and findings to consider how calorie-labeling policy could be improved for greater impact.

The objective was to detect geospatial clustering of sugar-sweetened beverage (SSB) intake in Boston adolescents (age = 16.3 +/- 1.3 years [range: 13-19]; female = 56.1%; White = 10.4%, Black = 42.6%, Hispanics = 32.4%, and others = 14.6%) using spatial scan statistics. We used data on self-reported SSB intake from the 2008 Boston Youth Survey Geospatial Dataset (n = 1292). Two binary variables were created: consumption of SSB (never versus any) on (1) soda and (2) other sugary drinks (e.g., lemonade). A Bernoulli spatial scan statistic was used to identify geospatial clusters of soda and other sugary drinks in unadjusted models and models adjusted for age, gender, and race/ethnicity. There was no statistically significant clustering of soda consumption in the unadjusted model. In contrast, a cluster of non-soda SSB consumption emerged in the middle of Boston (relative risk = 1.20, p = .005), indicating that adolescents within the cluster had a 20% higher probability of reporting non-soda SSB intake than outside the cluster. The cluster was no longer significant in the adjusted model, suggesting spatial variation in non-soda SSB drink intake correlates with the geographic distribution of students by race/ethnicity, age, and gender.

OBJECTIVE:To identify demographic and consumer characteristics associated with refilling a soft drink at fast-food restaurants and the estimated energy content and volume of those refills. DESIGN/METHODS:Logistic and linear regression with cross-sectional survey data. SETTING/METHODS:Data include fast-food restaurant receipts and consumer surveys collected from restaurants in New York City (all boroughs except Staten Island), and Newark and Jersey City, New Jersey, during 2013 and 2014. SUBJECTS/METHODS:Fast-food restaurant customers (n 11795) from ninety-eight restaurants. RESULTS:Thirty per cent of fast-food customers ordered a refillable soft drink. Nine per cent of fast-food customers with a refillable soft drink reported refilling their beverage (3 % of entire sample). Odds of having a beverage refill were higher among respondents with a refillable soft drink at restaurants with a self-serve refill kiosk (adjusted OR (aOR)=7·37, P<0·001) or who ate in the restaurant (aOR=4·45, P<0·001). KFC (aOR=2·18, P<0·001) and Wendy's (aOR=0·41, P<0·001) customers had higher and lower odds, respectively, of obtaining a refill, compared with Burger King customers. Respondents from New Jersey (aOR=1·47, P<0·001) also had higher odds of refilling their beverage than New York City customers. Customers who got a refill obtained on average 29 more 'beverage ounces' (858 ml) and 250 more 'beverage calories' (1046 kJ) than customers who did not get a refill. CONCLUSIONS:Refilling a beverage was associated with having obtained more beverage calories and beverage ounces. Environmental cues, such as the placement and availability of self-serve beverage refills, may influence consumer beverage choice.

OBJECTIVE: To use novel geographic methods and large-scale claims data to identify the local distribution of pediatric chronic diseases in New York City. METHODS: Using a 2009 all-payer emergency claims database, we identified the proportion of unique children aged 0 to 17 with diagnosis codes for specific medical and psychiatric conditions. As a proof of concept, we compared these prevalence estimates to traditional health surveys and registry data using the most geographically granular data available. In addition, we used home addresses to map local variation in pediatric disease burden. RESULTS: We identified 549,547 New York City children who visited an emergency department at least once in 2009. Though our sample included more publicly insured and uninsured children, we found moderate to strong correlations of prevalence estimates when compared to health surveys and registry data at prespecified geographic levels. Strongest correlations were found for asthma and mental health conditions by county among younger children (0.88, P = .05 and 0.99, P < .01, respectively). Moderate correlations by neighborhood were identified for obesity and cancer (0.53 and 0.54, P < .01). Among adolescents, correlations by health districts were strong for obesity (0.95, P = .05), and depression estimates had a nonsignificant, but strong negative correlation with suicide attempts (-0.88, P = .12). Using SaTScan, we also identified local hot spots of pediatric chronic disease. CONCLUSIONS: For conditions easily identified in claims data, emergency department surveillance may help estimate pediatric chronic disease prevalence with higher geographic resolution. More studies are needed to investigate limitations of these methods and assess reliability of local disease estimates.

Purpose . Interest and funding continue to grow for bringing supermarkets to underserved areas, yet little is known about their impact. Design . A quasi-experimental study was used to determine the impact of a new supermarket opening as a result of tax and zoning incentives. Setting . The study took place in the South Bronx, New York City, New York. SUBJECTS: Studied were residents of two South Bronx neighborhoods deemed high need. Measures . Food purchasing and consumption were examined via surveys and 24-hour dietary recalls before and at two points after the supermarket opened (1-5, 13-17 months). Analysis . Data were analyzed using difference-in-difference models controlling for gender, race and ethnicity, age, education, marital status, and self-reported income. Ordinary least squares and logistic regression models were estimated for continuous and binary outcomes, respectively. Results . At baseline, 94% to 97% of consumers shopped at a supermarket. There was a 2% increase in this behavior in the intervention community (p < .05) not seen in the comparison community. One year later there was a 7% net increase in eating at home (p < .1) and a 20% decrease in drinking sugary beverages (p < .05), but no appreciable change in fruit/vegetable consumption or overall dietary quality. Conclusion . The new supermarket did not result in substantial or broad changes in purchasing patterns or nutritional quality of food consumed, though smaller, positive changes were observed over a 1-year period. Future work should examine different contexts and a broader set of outcomes, including economic development.