At Risk Populations for Severe COVID-19, part II

We have continued to work with‘s excellent data portal tool to map populations at risk of severe COVID-19.  Our prior post is here.  The map below shows Counties in purple with high numbers of adults 65 years or older and low availability of hospital beds.  High numbers of adults 65 years or older was defined as more the U.S. median across counties (greater than 4,698 people) and low availability was defined as less than the median number of hospital beds (<49 beds).  Population counts are from the Census Bureau for 2014-2018 and counts of hospital beds are from the Health Resources and Services Administration (HRSA) for 2016.

Counties in purple have large populations of older adults and low numbers of hospital beds.

Posted in Adults, Community Needs Assessment, Health Care Access | Leave a comment

At Risk Populations for Severe COVID-19

Like the vast majority of the world, we have been obsessing over the COVID-19 pandemic.  Given that certain populations are at risk for severe COVID-19 disease we have been wondering where the at risk populations are in the U.S.  To generate some quick maps we used‘s excellent data portal and mapping tool. By county, we mapped the number of people 65 years and older, 75 years and older and the numbers of people with underlying chronic conditions linked to severe COVID-19 disease.  Counts of people rather than percentages of the population were mapped because it is the number of people, not the percent, that can strain the health care system.  We also mapped the number of hospital beds – note that at any given time in the U.S. about 66% of beds are occupied by patients.


Posted in Adults, Community Needs Assessment, Health Care Access | Leave a comment

Measuring Neighborhood Walkability across Communities in the U.S. Over the Past Three Decades

The evidence on links between neighborhood walkability and physical activity and body mass index remains limited because there have been few longitudinal studies with repeated measures of neighborhood walkability and health behavior and outcomes.  While large cohort studies with long-term follow-up, residential address history, and health outcomes are available, the lack of neighborhood walkability measures with the same temporal and geographic coverage limits the use of these cohorts to study how urban form shapes health.  We recently published a paper in the Journal of Urban Health describing a new measure of neighborhood walkability, the Built Environment and Health-Neighborhood Walkability Index (BEH-NWI), that can be calculated across communities in the U.S. and historically over the past three decades.

We retrospectively measured neighborhood walkability for 2010 for 1 km circles centered on each Census block in NYC (N=38,526) using the BEH-NWI and using our prior NWI.  The correlation between walkability scores calculated from our BEH-NWI and our prior NWI across NYC is 86%, and BEH-NWI scores across NYC are also highly correlated with circa 2010 WalkScore data.

We used the BEH-NWI with two studies that previously collected physical activity, health and residential address data, the NYU Women’s Health Study and the NYC Department of Health and Mental Hygiene’s 2011 Physical Activity and Transit (PAT) Survey.  We calculated BEH-NWI scores for the residential neighborhoods of participants in the NYU Women’s Health Study when they first enrolled into the study circa 1990.  Higher BEH-NWI scores were significantly associated with greater self-reported walking per week and lower body mass index among study participants.  PAT Survey participant’s wore accelerometers for a week to objectively measure their physical activity and we found that higher BEH-NWI scores were significantly associated higher levels of physical activity.  BEH-NWI scores and WalkScore data were equivalently predictive of total physical activity among PAT Survey participants, but the BEH-NWI has the advantage that it can be retrospectively calculated across the U.S. back to 1990.

Differences in BMI by Quartile of Residential Neighborhood Walkability among NYU Women’s Health Study participants circa 1990.

The BEH-NWI can be a valuable new resource for research on how urban form and built environments affect physical activity, obesity, and health. The BEH-NWI is grounded conceptually in urban planning/design theory and uses data that are available nationwide and historically as far back as 1990. This measure will allow researchers to leverage existing longitudinal human health datasets for new insights into the role of neighborhood features in shaping health.

Posted in Accelerometers, Active Transport, Adults, Methods, Physical Activity, Urban Design, Walkability | Leave a comment

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.

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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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