A lot of us in the neighborhood health effects field create or use neighborhood contextual measures that are aggregations of population data from the Census or other large social surveys. For instance, common measures of neighborhood level socio-economic status, such as poverty rate, per capita income, and median household income, are all derived from Census data on individual respondents’ self-reported household income. Our recent work has asked the question: what is the effect on our estimates of association between a neighborhood level socioeconomic variable and an individual level health outcome when the individual self-reports on income to the Census include random measurement error? Continue reading
There Goes the Neighborhood Effect: measurement error in the construction of neighborhood contextual measures
Preventive Medicine just published our paper on neighborhood park access and BMI among residents of New York City. These analyses were part of our ongoing work the New York City Department of Health and Mental Hygiene to analyze their health surveillance data in conjunction with measures of neighborhood context. In this report we showed that higher neighborhood park access and the quality of those parks (extent to which parks were free of graffiti, litter, trash and broken glass) were associated with lower BMI scores among residents. This report also showed that higher neighborhood walkability was associated with lower BMI, while neighborhood poverty and homicide rates were associated with higher BMI for residents.
The graph below plots, after adjustment for differences in survey respondent’s socio-demographic characteristics, the difference in BMI, and the 95% confidence interval, associated with differences equivalent to the inter-quartile range in neighborhood conditions across NYC zip codes.
The NYC Department of Health and Mental Hygiene just released a Data Brief describing our collaborative research using data from the Physical Activity and Transit (PAT) Survey to study neighborhood walkability and physical activity in NYC. This survey used GPS and accelerometer devices to measure physical activity for up to seven days and allows us to understand how residents use their neighborhoods and how much activity occurs in different settings across NYC. Compared to survey respondents living in neighborhoods the lowest quartile of neighborhood walkability, those that lived in neighborhoods in the highest quartile engaged in 100 additional minutes of moderate equivalent activity per week. More details about our work on the project can be seen here.
Streetsblog NYC posted about the Data Brief and some of the other work we have been doing on walkability in NYC.
Andrew Rundle presented recent work by BEH on food environments in New York City at the New York City Food Policy Center at Hunter College’s event “Food Policy for Breakfast: Food Policy Research in NYC- What do we know? Where do we need to go?”. Hunter College posted video from the event to YouTube, including Dr. Rundle’s talk and the group Q&A and discussion.
Q&A and Discussion part 1
Q&A and Discussion part 2
We are happy to share a python script that downloads and compiles all of the current and archived New York City (NYC) Department of City Planning’s (DCP) MapPluto versions into a single file geodatabase with feature datasets for each year-version. BEH GIS team developed the script to save time and effort in downloading, unzipping and merging all this data by hand. We hope this script will save time for anyone else who wishes to compile all this data. The script is based on an in-house urllib script for mining tract shapefiles by state from the US Census Bureau and was developed by Daniel Sheehan.
More about the public release of MapPLUTO data…
While most of our work to date has been concerned with physical activity, obesity and asthma, the built environment can also shape injury risk. Nearly 5,000 pedestrians in the U.S. are killed by motor vehicles ever year, and a small number of high-risk intersections account for a substantial proportion of vehicle-pedestrian collisions. Modification of the road and pedestrian environment where collisions occur is an attractive potential intervention both to save lives and to promote pedestrian and cycling activity (active transport). Previous research on the relationship between pedestrian environment characteristics and collision risk has uncovered counter-intuitive findings, including that crosswalks may pose an increase in risk to older pedestrians, but research on pedestrian injuries has been limited due, in part, to the high cost of visiting collision sites and comparison intersections to collect data on intersection characteristics.
We were recently awarded a pilot grant from the Center for Injury Epidemiology and Prevention at Columbia University Medical Center to investigate the relationship between pedestrian environment characteristics in New York City, as assessed using our CANVAS tool, and the risk of a pedestrian-motor vehicle collision serious enough to warrant a police report. Using CANVAS, we expect to be able to collect data much more efficiently than in-person audits have been able to, unlocking a new data source to understand which intersection modifications can best reduce collisions between cars and people.
Out of the 643 entries submitted to the Knight Foundation News Challenge, our project “Open CANVAS: A Web Application Harnessing Google Street View to Collect and Share Data on Neighborhoods” was one of the 40 projects selected as finalists. Each team was asked to revise their projects for the next round of review and to make a 30 second video explaining the project. Here is what we came up with…
A ‘making of the video’ blog post is here.
In urban areas such as New York City, many corner stores (“bodegas”) offer prepared or ready-to-eat food. In studies of the food environment, researchers usually consider bodegas as grocery stores, and compare them with large stores such as supermarkets. But many bodegas sell packaged ready-to-eat items or prepared food from deli counters, salad bars, or steam tables – in other words, they fill a similar niche in the food environment as fast food or take-out restaurants. What would happen, we wondered, if we compared the nutritional environment of bodegas to that of another outlet type well-known for offering inexpensive and convenient food – national chain fast food restaurants?
With support from an ARRA supplement to our grant from NIDDK, as well as from the ISERP summer intern program, we sent five student interns into the field to find out. We used the NEMS-R (Nutrition Environment Measurement Study for Restaurants) audit protocol for both fast-food restaurants and bodegas. A widely used tool for evaluating nutrition environments, the NEMS-R measures the availability of healthy food and beverages (e.g. fresh fruit, low-fat milk). It also looks for ways a food outlet might prompt or incentivize healthy or unhealthy eating, for instance by providing calorie counts or offering “all you can eat” specials. Along with Laszlo Lovasi and Karla Milinkovic, who managed the fieldwork, the students audited more than 200 bodegas and fast-food outlets in Manhattan, Brooklyn, and the Bronx. Continue reading
Our Entry for the Knight News Challenge: How can we harness data and information for the health of communities?
We entered a project into the Knight News Foundation Challenge: How can we harness data and information for the health of communities? Our proposal is to further develop our CANVAS: Street View project and make it available to researchers, agencies and community groups so they can easily use our system to run neighborhood data collection studies from anywhere in the world. You can see our project here. Please check it out and hit the “applause” button.
Our submission was motivated by a proposed research case-study to use CANVAS to identify characteristics of intersections that put pedestrians at risk of injury or death. Approximately 5,000 pedestrians in the US are killed by motor vehicles ever year and many fold more are injured.
We have continued our work studying the food environment in NYC, developing measures that take a more ecosystem perspective on neighborhood food environments. For each zip code, we measured the density of food outlets, the proportion of retail food outlets that were BMI-healthy (supermarkets, fruit and vegetable markets, natural food stores) or BMI-unhealthy (local and national fast food restaurants, pizza restaurants, convenience stores, bodegas, bakeries, candy and nut stores, meat markets) and the overall diversity of the food environment.