A Driver in Health Outcomes: Developing Discrete Categories of Transportation Insecurity.

Research suggests that transportation is an important social determinant of health, because the ability to get around is consequential for accessing health care and nutritious food and for making social connections. We used an inductive mixed-methods approach and a quantitative k-means clustering approach to identify 5 categories of transportation insecurity using the validated 16-item Transportation Security Index. The resulting 5-category measure distinguished among respondents with qualitatively different experiences of transportation insecurity.

Causal Inference with Case-Only Studies in Injury Epidemiology Research.

Purpose Of Review: We review the application and limitations of two implementations of the "case-only design" in injury epidemiology with example analyses of Fatality Analysis Reporting System data.

Recent Findings: The term "case-only design" covers a variety of epidemiologic designs; here, two implementations of the design are reviewed: (1) studies to uncover etiological heterogeneity and (2) studies to measure exposure effect modification. These two designs produce results that require different interpretations and rely upon different assumptions.

Exploring potential for selection bias in using survey data to estimate the association between institutional trust and depression.

Purpose: We tested the hypothesis that low institutional trust would be associated with depressive symptom elevation, with attention to potential selection bias.

Methods: The District of Columbia Area Survey (DCAS) was conducted by mail in 2018. Invitations sent to 8800 households resulted in a sample of 1061 adults.

Machine Learning Approaches for Measuring Neighborhood Environments in Epidemiologic Studies.

Purpose Of Review: Innovations in information technology, initiatives by local governments to share administrative data, and growing inventories of data available from commercial data aggregators have immensely expanded the information available to describe neighborhood environments, supporting an approach to research we call Urban Health Informatics. This review evaluates the application of machine learning to this new wealth of data for studies of the effects of neighborhood environments on health.

Recent Findings: Prominent machine learning applications in this field include automated image analysis of archived imagery such as Google Street View images, variable selection methods to identify neighborhood environment factors that predict health outcomes from large pools of exposure variables, and spatial interpolation methods to estimate neighborhood conditions across large geographic areas.

The Disclosure of Personally Identifiable Information in Studies of Neighborhood Contexts and Patient Outcomes.

Clinical epidemiology and patient-oriented health care research that incorporates neighborhood-level data is becoming increasingly common. A key step in conducting this research is converting patient address data to longitude and latitude data, a process known as geocoding. Several commonly used approaches to geocoding (eg, ggmap or the tidygeocoder R package) send patient addresses over the internet to web-based third-party geocoding services.

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.

Street Audits to Measure Neighborhood Disorder: Virtual or In-Person?

Neighborhood conditions may influence a broad range of health indicators, including obesity, injury, and psychopathology. In particular, neighborhood physical disorder-a measure of urban deterioration-is thought to encourage crime and high-risk behaviors, leading to poor mental and physical health. In studies to assess neighborhood physical disorder, investigators typically rely on time-consuming and expensive in-person systematic neighborhood audits.

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.

Use of Google Street View to Assess Environmental Contributions to Pedestrian Injury.

Objectives: To demonstrate an information technology-based approach to assess characteristics of streets and intersections associated with injuries that is less costly and time-consuming than location-based studies of pedestrian injury.

Methods: We used imagery captured by Google Street View from 2007 to 2011 to assess 9 characteristics of 532 intersections within New York City. We controlled for estimated pedestrian count and estimated the relation between intersections' characteristics and frequency of injurious collisions.

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.

Development and deployment of the Computer Assisted Neighborhood Visual Assessment System (CANVAS) to measure health-related neighborhood conditions.

Public health research has shown that neighborhood conditions are associated with health behaviors and outcomes. Systematic neighborhood audits have helped researchers measure neighborhood conditions that they deem theoretically relevant but not available in existing administrative data. Systematic audits, however, are expensive to conduct and rarely comparable across geographic regions.

Validity of an ecometric neighborhood physical disorder measure constructed by virtual street audit.

Neighborhood physical disorder is thought to affect mental and physical health, but it has been difficult to measure objectively and reliably across large geographical areas or multiple locales. Virtual street audits are a novel method for assessing neighborhood characteristics. We evaluated the ecometric properties of a neighborhood physical disorder measure constructed from virtual street audit data.

CREATING MEASURES OF THEORETICALLY RELEVANT NEIGHBORHOOD ATTRIBUTES AT MULTIPLE SPATIAL SCALES.

Accurately measuring attributes in neighborhood environments allows researchers to study the influence of neighborhoods on individual-level outcomes. Researchers working to improve the measurement of neighborhood attributes generally advocate doing so in one of two ways: improving the theoretical relevance of measures and correctly defining the appropriate spatial scale. The data required by the first, "ecometric" neighborhood assessments on a sample of neighborhoods, are generally incompatible with the methods of the second, which tend to rely on population data.

The impact of neighborhood park access and quality on body mass index among adults in New York City.

Objective: To evaluate the association between adult individuals' body mass index (BMI) and characteristics of parks (size and cleanliness) in an urban environment taking into account the physical and social environments of the neighborhood.

Methods: Cross-sectional, hierarchical linear models were used to determine whether park effects were associated with BMI using self-reported height and weight data obtained from the Community Health Survey in New York City (2002-2006).

Results: Both the proportion of the residential zip code that was large park space and the proportion that was small park space had significant inverse associations with BMI after controlling for individual socio-demographic and zip code built environment characteristics (-0.

Comparing nutrition environments in bodegas and fast-food restaurants.

Many small grocery stores or "bodegas" sell prepared or ready-to-eat items, filling a niche in the food environment similar to fast-food restaurants. However, little comparative information is available about the nutrition environments of bodegas and fast-food outlets. This study compared the nutrition environments of bodegas and national chain fast-food restaurants using a common audit instrument, the Nutrition Environment Measures Study in Restaurants (NEMS-R) protocol.

Neighbourhood food environments and body mass index among New York City adults.

Background: Studies evaluating the impact of the neighbourhood food environment on obesity have summarised the density or proximity of individual food outlets. Though informative, there is a need to consider the role of the entire food environment; however, few measures of whole system attributes have been developed. New variables measuring the food environment were derived and used to study the association with body mass index (BMI).

More neighborhood retail associated with lower obesity among New York City public high school students.

Policies target fast food outlets to curb adolescent obesity. We argue that researchers should examine the entire retail ecology of neighborhoods, not just fast food outlets. We examine the association between the neighborhood retail environment and obesity using Fitnessgram data collected from 94,348 New York City public high school students.

Associations between body mass index and park proximity, size, cleanliness, and recreational facilities.

Purpose: To determine whether body mass index (BMI) is associated with proximity to neighborhood parks, the size of the parks, their cleanliness, and the availability of recreational facilities in the parks.

Design: Cross-sectional.

Setting: New York City.

Individual- and school-level sociodemographic predictors of obesity among New York City public school children.

To identify student- and school-level sociodemographic characteristics associated with overweight and obesity, the authors conducted cross-sectional analyses of data from 624,204 public school children (kindergarten through 12th grade) who took part in the 2007-2008 New York City Fitnessgram Program. The overall prevalence of obesity was 20.3%, and the prevalence of overweight was 17.

Body mass index, safety hazards, and neighborhood attractiveness.

Background: Neighborhood attractiveness and safety may encourage physical activity and help individuals maintain a healthy weight. However, these neighborhood characteristics may not be equally relevant to health across all settings and population subgroups.

Purpose: To evaluate whether potentially attractive neighborhood features are associated with lower BMI, whether safety hazards are associated with higher BMI, and whether environment-environment interactions are present such that associations for a particular characteristic are stronger in an otherwise supportive environment.

Neighborhood walkability and active travel (walking and cycling) in New York City.

Urban planners have suggested that built environment characteristics can support active travel (walking and cycling) and reduce sedentary behavior. This study assessed whether engagement in active travel is associated with neighborhood walkability measured for zip codes in New York City. Data were analyzed on engagement in active travel and the frequency of walking or biking ten blocks or more in the past month, from 8,064 respondents to the New York City 2003 Community Health Survey (CHS).

Retail grocery store marketing strategies and obesity: an integrative review.

Context: In-store food marketing can influence food-purchasing behaviors and warrants increased attention given the dramatic rise in obesity. Descriptive and experimental studies of key marketing components have been conducted by consumer scientists, marketing researchers, and public health experts. This review synthesizes research and publications from industry and academic sources and provides direction for developing and evaluating promising interventions.