View of a favella in Rio
The global rise of informal settlements have brought unique health challenges into the heart of urban centers. It is estimated that 2 billion people will live in informal urban settlements by 2030. The 2014 World Cup and the 2016 Olympics have brought renewed recognition of the informal favella communities of Brazil.
Led by Dr. Gina Lovasi, we have teamed up with an interdisciplinary group of global experts to perform an initial community needs assessment in Rio das Pedras, Rio de Janeiro, Brazil to assess the feasibility of large scale data collection on health, mobility, and the microbiome in these settings.
Informal distribution of electricity in Rio das Pedras
Rio das Pedras is the third largest informal community in Rio de Janeiro, Brazil. Home to approximately 63,500 individuals, Rio das Pedras is a vibrant community, however residents of this favela face seasonal flooding, vehicle traffic, improvised construction methods, and limited waste disposal. These factors, coupled with limited access to municipal services and transportation likely predispose residents to injury and poor health. However, little reliable data exists that can accurately characterize the health of residents of Rio das Pedras, and fewer data that can point out areas of intervention that will be most impactful in these settings. As a result, little is known regarding the present health risks that exist throughout the community.
Through an initial community health diagnosis, our team will map the mobility and public health resources driving population health patterns across the favela. The team will also take an initial look at the microbiome of informal settlements and analyze the quality and use of water throughout Rio das Pedras. This preliminary needs assessment will begin to create a health profile of the population and highlight the areas of intervention that can most improve the health and living conditions of the residents of Rio das Pedras and surrounding areas of Rio de Janeiro. Ultimately, this pilot will tailor and test a set of methods so future data collection efforts will more accurately reflect the needs of vulnerable populations living in these complex settings.
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
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.
Neighborhood Walkability in New York City
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.
Click the link to get the Script
Click the link to get the Readme
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
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.
The CANVAS web application uses Google Street View imagery to gather neighborhood data. In this case-study we illustrate the assessment of intersection design at pedestrian injury hotspots in NYC.