Currently there are 3936 grocery stores in NYC.
A community’s standard of living is directly related to the quality and quantity of resources available to them. Community health outcomes depend on the nutritional resources available to every individual. To protect citizens’ health, we must identify and rectify the systemic behaviors which contribute to nutritional inequity.
What does nutritional accessibility look like in NYC?
Data from Reference USA downloaded November 2020
Specifically, we focused on the 564,301 people living in the 302 public housing developments that currently exist in NYC.
Data from NYC Open Data
In order to interpret accessibility, we calculated the distance to every grocery store within a 30 minute walk radius of every public housing development.
We then used this data to count the number of grocery stores that can be reached in 30 minutes as well as 10 minutes.
This public housing development in Lower East Side, Manhattan has access to:
20 grocery stores within a 10 minute walk
134 grocery stores within a 30 minute walk
This public housing development in Dongan Hills, Staten Island has access to:
0 grocery stores within a 30 minute walk
The graph on the left shows the frequency of the grocery store counts for the 10 minute radius and the 30 minute radius.
For example, 36 public housing developments have access to 6 grocery stores in 10 minutes.
In order to compare access among public housing developments, we looked at both the number of grocery stores that exist within the 10 minute radius as well as the travel times to all grocery stores within the 30 minute radius.
The percentile on the 10 Minutes map is derived from the number of grocery stores that can be accessed in 10 minutes
The score on the 30 Minutes map is calculated by weighting all of the grocery stores that can be reached in 30 minutes. Grocery stores that are under 10 minutes away are given a weight of 1 while stores that are 10-30 minutes away are weighted on a linearly decreasing scale. This score is normalized to a percentage relative to the largest score.
The circles are colored according to percentile/score with darker colors indicating a higher percentile/score.
click on circles for more information
Though we hope regular citizens use our interactive maps to visualize nutrition access in their localities within NYC, our analysis is primarily intended for public institutions, policymakers and urban planners. Specifically, our goal is to present additional methods of policy analysis, with a focus on accessibility.
The spatial analysis conducted herein can provide a framework for answering questions such as “how do we more fully capture quality of living in public housing developments,” “how do we measure connectivity from a home to local amenities,” and “how can we propose locations for living residences and commercial retailers that maximize benefit for local communities?” We hope to encourage computational methods as tools for designing accessible cities.
Our analysis investigates the implementation of a public service, and as such there exists the possibility that any party could use our findings to advocate against public housing. To this end, we emphasize that our analysis does not focus on the salience of public housing efforts, but instead whether the built environment surrounding these developments provide their residents with appropriate food access. It is our belief that housing is a human right, and protecting that right requires ensuring people have access to food as well.
In reducing geometries to points, we lose the ability to consider a housing development’s size while calculating our iso-areas. As a specific example, the Breukelen Houses in Brooklyn have a total area of 2,830,416 square feet which mostly covers the ten minute radius.
By focusing on time measurements, we inherently ignore factors such as store pricing and sales volume, which are important considerations for accurately describing nutritional access.
Our analysis investigates the presence of disparate grocery store access, but does not offer suﬀicient quantitative insight towards promoting nutritional equity. As presented, it is not entirely clear as to whether housing developments or grocery stores (or both) have been misplaced or “misplanned.”
To provide a more comprehensive analysis, we would like to investigate which demographic factors are correlated with nutritional access. Specifically, we would like to consider census geometries and American Community Survey demographic estimates. Using classification methods such as logistic regression would allow us to determine how factors such as average income, age, and race correlate with nutritional access.
In addition to extending our numerical interpretation of accessibility, we would also like to better understand the behaviors of interaction between citizens and grocery stores to identify which characteristics of a grocery store define its impact on local nutrition access.
This further inquiry would entail researching the mechanics of grocery supply chains, economic evolution of American cities, and how multinational corporations influence or disrupt nutrition accesibility in different communities. We can pair this literature review with a regression analysis which relates store traﬀic to certain features such as sales volume and employee count.
By enhancing our understanding of the interaction between people and grocery stores, we can perform a more informed quantitive investigation of nutritional access, and identify demographic trends and causal behaviors.