Disparities in trajectories of changes in the unhealthy food environment in New York City: A latent class growth analysis, 1990-2010.

Disparities in availability of food retailers in the residential environment may help explain racial/ethnic and socio-economic differences in obesity risk. Research is needed that describes whether food environment dynamics may contribute to equalizing conditions across neighborhoods or to amplifying existing inequalities over time. This study improves the understanding of how the BMI-unhealthy food environment has evolved over time in New York City. We use longitudinal census tract-level data from the National Establishment Time-Series (NETS) for New York City in the period 1990-2010 and implement latent class growth analysis (LCGA) to (1) examine trajectories of change in the number of unhealthy food outlets (characterized as selling calorie-dense foods such as pizza and pastries) at the census tract-level, and (2) examine how trajectories are related to socio-demographic characteristics of the census tract. Overall, the number of BMI-unhealthy food outlets increased between 1990 and 2010. We summarized trajectories of evolutions with a 5-class model that indicates a pattern of fanning out, such that census tracts with a higher initial number of BMI-unhealthy food outlets in 1990 experienced a more rapid increase over time. Finally, fully adjusted logistic regression models reveal a greater increase in BMI-unhealthy food outlets in census tracts with: higher baseline population size, lower baseline income, and lower proportion of Black residents. Greater BMI-unhealthy food outlet increases were also noted in the context of census tracts change suggestive of urbanization (increasing population density) or increasing purchasing power (increasing income).

Neighborhood Recreation Facilities and Facility Membership Are Jointly Associated with Objectively Measured Physical Activity.

Efforts to increase physical activity have traditionally included either individual-level interventions (e.g., educational campaigns) or neighborhood-level interventions (e.g., additional recreational facilities). Little work has addressed the interaction between spatial proximity and individual characteristics related to facility use. We aimed to better understand the synergistic impact of both physical activity environments and recreational facility membership on objectively measured physical activity. Using the New York City Physical Activity and Transit (PAT) survey (n = 644), we evaluated associations between counts of commercial physical activity facilities within 1 km of participants' home addresses with both facility membership and accelerometry-measured physical activity. Individuals living near more facilities were more likely to report membership (adjusted odds ratio for top versus bottom quartile of facility count: 3.77 (95% CI 1.54-9.20). Additionally, while amount of facilities within a neighborhood was associated with more physical activity, this association was stronger for individuals reporting gym membership. Interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership. Evaluation of neighborhood opportunities must expand beyond physical presence to consider multiple dimensions of accessibility.

Exploring the Health and Spatial Equity Implications of the New York City Bike Share System.

INTRODUCTION: This paper examines spatial equity and estimates the health impact of Citi Bike, New York City's (NYC) bike share system. We discuss how further system expansion and utilization by residents in high-poverty communities of color could affect the potential benefit of the largest bicycle share system in the United States. METHODS: First, we compared the Citi Bike station distribution by census tract poverty during the system's 2013 launch and after the 2015 geographic expansion. Second, we applied the World Health Organization's Health Economic Assessment Tool (HEAT) to estimate the benefit of cycling associated with annual Citi Bike members for two 12-month time periods and analyzed change of the benefit over time. RESULTS: The results showed that the greatest proportion of Citi Bike stations were located in low-poverty (wealthier) NYC census tracts (41% per period), and there were no significant changes in station distribution during expansion. HEAT estimated an increase from two to three premature deaths prevented and an increased annual economic benefit from $18,800,000 to $28,300,000 associated with Citi Bike use. CONCLUSION: In conclusion, although Citi Bike stations are not equitably located, the estimated annual health benefits are substantial and have increased over time. Our findings underscore the potential for even greater benefits with increased spatial access in higher-poverty neighborhoods and communities of color. Our findings highlight the importance of the built environment in shaping health and the need for a health equity lens to consider the social and political processes that perpetuate inequities.

Neighborhood food environment, dietary fatty acid biomarkers, and cardiac arrest risk.

We explored links between food environments, dietary intake biomarkers, and sudden cardiac arrest in a population-based longitudinal study using cases and controls accruing between 1990 and 2010 in King County, WA. Surprisingly, presence of more unhealthy food sources near home was associated with a lower 18:1 trans-fatty acid concentration (-0.05% per standard deviation higher count of unhealthy food sources, 95% Confidence Interval [CI]: 0.01, 0.09). However, presence of more unhealthy food sources was associated with higher odds of cardiac arrest (Odds Ratio [OR]: 2.29, 95% CI: 1.19, 4.41 per standard deviation in unhealthy food outlets). While unhealthy food outlets were associated with higher cardiac arrest risk, circulating 18:1 trans fats did not explain the association.

Medical facilities in the neighborhood and incidence of sudden cardiac arrest.

BACKGROUND: Medical establishments in the neighborhood, such as pharmacies and primary care clinics, may play a role in improving access to preventive care and treatment and could explain previously reported neighborhood variations in sudden cardiac arrest (SCA) incidence and survival. METHODS: The Cardiac Arrest Blood Study Repository is a population-based repository of data from adult cardiac arrest patients and population-based controls residing in King County, Washington. We examined the association between the availability of medical facilities near home with SCA risk, using adult (age 18-80) Seattle residents experiencing cardiac arrest (n = 446) and matched controls (n = 208) without a history of heart disease. We also analyzed the association of major medical centers near the event location with emergency medical service (EMS) response time and survival among adult cases (age 18+) presenting with ventricular fibrillation from throughout King County (n = 1537). The number of medical facilities per census tract was determined by geocoding business locations from the National Establishment Time-Series longitudinal database 1990-2010. RESULTS: More pharmacies in the home census tract was unexpectedly associated with higher odds of SCA (OR:1.28, 95% CI: 1.03, 1.59), and similar associations were observed for other medical facility types. The presence of a major medical center in the event census tract was associated with a faster EMS response time (-53 s, 95% CI: -84, -22), but not with short-term survival. CONCLUSIONS: We did not observe a protective association between medical facilities in the home census tract and SCA risk, orbetween major medical centers in the event census tract and survival.

Neighborhood Physical Disorder in New York City.

Neighborhood physical disorder, or the deterioration of urban environments, is associated with negative mental and physical health outcomes. Eleven trained raters used CANVAS, a web-based system for conducting reliable virtual street audits, to collect data on nine indicators of physical disorder using Google Street View imagery of 532 block faces in New York City, New York, USA. We combined the block face indicator data into a disorder scale using item response theory; indicators ranged in severity from presence of litter, a weak indicator of disorder, to abandoned cars, a strong indicator. Using this scale, we estimated disorder at the center point of each sampled block. We then used ordinary kriging to interpolate estimates of disorder levels throughout the city. The resulting map condenses a complex estimation process into an interpretable visualization of the spatial distribution of physical disorder in New York City.

Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set.

BACKGROUND: The densities of food retailers, alcohol outlets, physical activity facilities, and medical facilities have been associated with diet, physical activity, and management of medical conditions. Most of the research, however, has relied on cross-sectional studies. In this paper, we assess methodological issues raised by a data source that is increasingly used to characterize change in the local business environment: the National Establishment Time Series (NETS) dataset. DISCUSSION: Longitudinal data, such as NETS, offer opportunities to assess how differential access to resources impacts population health, to consider correlations among multiple environmental influences across the life course, and to gain a better understanding of their interactions and cumulative health effects. Longitudinal data also introduce new data management, geoprocessing, and business categorization challenges. Examining geocoding accuracy and categorization over 21 years of data in 23 counties surrounding New York City (NY, USA), we find that health-related business environments change considerably over time. We note that re-geocoding data may improve spatial precision, particularly in early years. Our intent with this paper is to make future public health applications of NETS data more efficient, since the size and complexity of the data can be difficult to exploit fully within its 2-year data-licensing period. Further, standardized approaches to NETS and other "big data" will facilitate the veracity and comparability of results across studies.