How did the unhealthy food environment evolve in New York City?

BEH collaborator Nico Berger and BEH member Gina Lovasi recently led a study on changes in the unhealthy retail food environment in New York City. The study found that the number of food outlets selling calorie-dense foods such as pizza and pastries dramatically increased between 1990 and 2010. Differences in trajectories were observed across neighborhoods: neighborhoods with a higher initial number of unhealthy food outlets in 1990 experienced a more rapid increase over time. Greater increase in unhealthy food outlets were observed in neighborhood with higher population size, lower income, and lower proportion of Black residents. Greater unhealthy food outlet increases were also noted in the context of neighborhood change suggestive of urbanization (increasing population density) or increasing purchasing power (increasing income).

This study used longitudinal data from the National Establishment Time-Series (NETS), a large historical dataset of retail businesses.  The number of retail outlets classified as selling “BMI-unhealthy” foods was counted every year at the census tract-level. BMI-unhealthy food outlets included convenience stores, “bodegas” or very small grocery stores, fast food restaurants, pizza restaurants, bakery or candy/confectionery stores, and meat markets.

Trajectories of changes were analyzed using Latent Class Growth Analysis in order to identify neighborhoods with similar patterns of changes.  The analyses identified five latent classes, which can be thought of as typologies of neighborhood trajectories for the availability of BMI-unhealthy food retail.  The figure below shows the count of BMI-unhealthy retail outlets per year for each of the five latent classes.

This study concludes that initiatives to reduce neighborhood exposure to unhealthy food should focus on disadvantaged neighborhoods in order to reduce environmental and health disparities. Attention should be given to the broader retail business context to ensure changes do not have the unintended consequence of increased health disparities.

Posted in Food Environment, Social Determinants | Leave a comment

National Geographic Cities Issue

Just a quick note:  The April 2019 issue of National Geographic focuses on Cities and how to redesign them to support health, sustainability and community.  The issue covers transit oriented design, China’s new urban design regulations, walking through Tokyo, the evolution of a refugee settlement in Uganda into an urban hub and rats in NYC, all with Nat Geo’s excellent maps and info-graphics.  Check it out.

Nat Geo Cities Issue

Posted in Active Transport, Economic Development, Injury, Parks, Pedestrian Injury, Physical Activity, Safety, Transportation, Urban Design, Urban Forestry, Walkability | Leave a comment

How Do Gym Location and Membership Interact to Impact Physical Activity?

We recently published a paper in the Journal of Urban Health, led by BEH alum Tanya Kaufman and frequent BEH collaborator Jana A. Hirsch, which found that individuals living near more commercial physical activity facilities (e.g. health club, tennis club, martial arts school, dance studio) were more likely to report having a membership at a gym or recreational facility.  Additionally, while amount of facilities within a neighborhood was associated with more measured physical activity, this association was stronger for individuals who reported having a gym membership.

This study used the New York City Department of Health and Mental Hygiene’s “New York City Physical Activity and Transit (PAT)” survey data.  We evaluated associations between counts of commercial physical activity facilities (from the National Establishment Time Series database) within 1 km of participants’ home addresses with both facility membership and accelerometry-measured physical activity.

Often efforts to increase physical activity have focused on either individuals (e.g., educational campaigns) or neighborhoods (e.g., access to additional recreational facilities). Little work looks at the interaction between spatial proximity (having a facility nearby) and individual characteristics that could be related to facility use. Our study findings suggest that interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership to the neighborhood amenities. Similarly, evaluation of neighborhood opportunities should expand beyond physical presence to consider other factors that make an amenity accessible to different populations.

Posted in Accelerometers, Physical Activity, Urban Forestry | Leave a comment

Teaching Epidemiology From High School Through Graduate School

Stark from his BEH days

BEH alumni, James Stark, recently published a paper in the American Journal of Epidemiology, “Teaching on the Continuum: Epidemiology Education From High School Through Graduate School“. This is the second in his planned trilogy of papers on epidemiology education.

In this article he and his co-authors propose an epidemiology learning continuum for students from high school through graduate school. They call for a student-centered instructional approach to best hone learners’ grasp of concepts and skills. Furthermore, they propose scaffolded learning to help epidemiology students to develop more advanced insights and abilities as they progress in the field.  They argue that their approach is aligned with the Association of Schools and Programs of Public Health’s “Framing the Future” initiative for public health education for the 21st century.

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Mobile Phone-Based Neighborhood Audits

We recently published a paper describing our efforts to adapt street audit strategies for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil.  We developed a smartphone-based systematic observation protocol to gather street-level information for a high-density convenience sample of street segments in RdP (N = 630, estimated as 86% of all street segments in the community).  The street audit protocol was built on the Fulcrum app deployed on smart phones and allowed street auditors to record observational data into forms on the phone’s screen and to capture geotagged images from the phone’s camera. The app also had a mapping interface to help guide the field team around RdP to the selected street segments that were being audited.

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Free-floating Bike Share in Seattle

BEH member Steve Mooney recently led two studies regarding the use of the free-floating bike share system in Seattle.  (Free-floating bike share systems are systems that allow users to pick up and leave bikes anywhere within a service area rather than at dedicated docking stations). These studies showed two things: a) that few people riding free-floating bike share rentals in Seattle are wearing helmets and b) that bikes were usually available in all Seattle neighborhoods across economic, racial and ethnic lines.

The helmet study, recently published in the Journal of Community Health, suggested that bike share systems, as compared with private bikes, may facilitate a more casual approach to cycling that makes helmet usage more challenging.  The team, mostly members of the INSIGHT program at the Harborview Injury Prevention & Research Center in Seattle, counted the number of cyclists – noting helmet use –at four strategic locations around Seattle: the Fremont bridge, the Burke-Gilman Trail, Broadway Bike Lane and NW 58th Street at 22nd Avenue NW.  They found that only one in five people riding bike shares wore helmets, as compared with nine in ten people riding private bikes.  Intriguingly, they also found that fewer private bike cyclists wore helmets in locations where there were more bike share users.

Other studies have found similarly low statistics of bike helmet use in other bike share systems, with about 15 percent helmet use in New York and about 39 percent in Boston compared with Seattle’s estimated 20 percent use of helmets. However, Vancouver’s system, Mobi, provides helmets and boosts usage there as much as three times Seattle, at 64 percent.

In a separate study, published recently in the Journal of Transport Geography, Mooney (and frequent BEH collaborator Jana Hirsch) again looked at bike share programs. This time they wanted to see if the benefits of bike share were available to all neighborhoods regardless of economic, racial and ethnic composition.  Prior studies have shown that docked bike share systems, which are geographically constrained by station locations, tend to favor advantaged neighborhoods.

What they found was nuanced: a baseline level of free-floating bikes were available in all neighborhoods across the city.  When they looked a little more closely at where bikes tended to be ridden to and ‘rebalanced’ to (i.e. where the operating companies moved the bikes around the city) and merged that with neighborhood based census data, they did find a higher concentration of bikes in more affluent areas of the city.  This inequity appeared to be driven by unequal demand across the city.  That is, bike share operators did a good job of rebalancing bikes to places where they did not remain idle long – but those places tended to have wealthier and more educated residents than the city as a whole.

Their future work will dig more deeply into barriers to bike share usage and how much the low helmet use affects injury risk.

Posted in Active Transport, Bike Share, Bikeshare, Injury, Physical Activity, Safety, Socioeconomic status, Transportation | Leave a comment

Launching the Interactive-Pedestrian Injury Mapper (I-PIM)

In 2015 in the U.S. 5,376 pedestrians were killed and 70,000 were injured. The Built Environment and Health Research Group has just launched the Interactive-Pedestrian Injury Mapper (I-PIM) website (HERE), to crowd source the collection of data on locations where pedestrians have been hit by automobiles.  Our goal is to collect location data on intersections where pedestrians have been injured so that built environment, side-walk and road-way risk factors for pedestrian injuries can be identified.

I-PIM has a Google maps based tool that allows a user to place a pin on the intersection or street where they were hit and to then map the route they walked prior to getting hit. I-PIM then asks some questions about the user, such as age and gender and then asks some questions about the collision, such as the type of vehicle that hit the person and whether they received medical care at the scene or had to go to the hospital.

Once injury location and route data from a lot of people have been entered into I-PIM, we plan to use Google Street View to virtually walk the routes and collision site and collect data on built environment, side-walk and road-way risk factors such as the presence of cross-walks, stop signs, visual distractions and blocked sight lines.  Our goal is to understand the ways in which pedestrian and roadway infrastructure at intersections that people crossed without being hit differs from intersections where they were hit.

If you have been hit by an automobile and would like to enter your information into I-PIM click HERE.

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How and where patterns of activity among older adults change over time

At BEH, we’re interested in how your residential neighborhood affects how physically active you are. But we’ve come to understand that being active as not just one thing and not merely a matter of expending calories. That is, walking is different from yoga is different from basketball is different from a seven-minute workout every morning.  They’re all activity, and for the most part, they’re all good for you, but two people could both meet the recommended number of minutes of activity per week, but arrive there through very different patterns of activity. We focus a lot on walking, because there’s extensive evidence that walking is one of the easiest ways to integrate activity into your daily life. As a result, we expect that making our cities more walkable could be a great way to get our population more active.

But for any given person, meeting activity recommendations may be easier for some activities than for others.  Few older adults play basketball, say, but a lot of older adults say they’d like low-cost, low-impact activities, like walking and gardening.  A few years ago, we started characterizing the patterns of types of activity older adults engage in, focusing on the NYCNAMES-II cohort, a cohort of older adults in New York we surveyed three times over five years. We found that adhering to specific patterns of activity predicted lower BMI better than simply analyzing total activity alone, and also explained prevalence of depressive symptoms. We also know this cohort’s neighborhood conditions (including neighborhood disorder, a conditionwe’vestudiedextensively) are correlated with their total activity and with their depressive symptoms.

So we thought we might learn something by looking at change through time in activity patterns in the NYCNAMES-II cohort, and whether those changes we correlated with neighborhood conditions.  In a paper that’s just hitting the web now at the American Journal of Epidemiology, we used a latent transition analysis to explore how the activity patterns of the study participants changed through time, and then explored individual and neighborhood predictors of those changes.

Activity classes are shown in boxes, and common transitions (among those who changed classes) are indicated by arrows between boxes

We found that there were 7 common activity patterns and that the most common changes between those patterns came from adding or removing one activity type (e.g. walking, sports & exercises, etc.). Neighborhood unemployment rate was the only neighborhood level factor we found to be consistently associated with transitioning between activity patterns.

Our results were encouraging. The latent transition analysis gave us a better picture of the kinds of changes older adults in New York City make in their activity, and we learned that, for example, engaging in gardening at any given time is not just a matter of having access to gardening space and an inclination to garden.  We anticipate that future latent transition analyses, with more people followed over more years could give us further insight into which activities we might suggest to which older adults to best increase population activity levels.

Posted in Adults, Methods, Physical Activity, Physical Disorder | Leave a comment

Neighborhood Conditions Influence the Ability of Diabetics to Control Their Blood Sugar

In collaboration with researchers from the New York City Department of Health and Mental Hygiene we recently published an article in the American Journal of Epidemiology showing that diabetics living in neighborhoods with more advantaged economic environments, greater walkability and healthier retail food environments have an improved ability to achieve glycemic control.  Hemoglobin A1C data from the New York City A1C Registry for 182,756 adults who had 1,273,801 A1C tests from 2007 to 2013 were analyzed along with data describing the neighborhood contexts they lived in.  The odds of individuals achieving glycemic control in the most advantaged residential neighborhoods (better economic conditions, greater walkability, healthier retail food profiles) was two and a half times greater than in the least advantaged.  Furthermore, individuals who lived in the most advantaged residential neighborhoods achieved glycemic control in a shorter period of time than individuals who lived in the least advantaged neighborhoods.  For those who moved during the 2007 to 2014 period, moving from less advantaged neighborhoods to more advantaged neighborhoods was associated with improved diabetes control, while moving from more advantaged areas to less advantaged areas was related to worsening diabetes control.  This is the first longitudinal study to examine the relationship between residential neighborhood environments and individual’s ability to control their diabetes.

Posted in Diabetes, Food Environment, Parks, Social Determinants, Socioeconomic status, Urban Design, Walkability | Leave a comment

Teaching Epidemiology to Undergraduate Students

Undergraduate programs in public health are proliferating (and see here), and increasing numbers of undergraduate students are receiving training in epidemiology.  James Stark, a BEH alum and now a Director of Epidemiology at Pfizer and Adjunct Professor at NYU’s College of Global Public Health, just published a paper in the American Journal of Epidemiology on approaches to teaching epidemiology at the undergraduate level.

Epidemiology courses introduce undergraduate students to a population health perspective and provide opportunities for these students to build essential skills and competencies such as ethical reasoning, teamwork, comprehension of scientific methods, critical thinking, quantitative and information literacy, ability to analyze public health information, and effective writing and oral communication.

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