Supermarket Location, Tranportation Options, and their relationship to Diet-Related Disease

Diet-Related Disease, Supermarket Location, and Access to Transportation

Options:Identifying food-critical areas and

vulnerable populations

Christopher BrideGEP690 – Capstone project

Dr. Andrew MarokoSpring 2012

© 2012 C.Bride

             Diet-Related Disease, Supermarket Location, and Access to Transportation Options:Identifying food-critical areas and vulnerable populations by Christopher P. Bride is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

Abstract

• This study is focused on identifying at risk populations for diet related disease through the analysis of census tract data, supermarket locations, and area hospital diagnostic (ICD-9) codes.

• The project is about population, not food deserts. An individual can live in a food desert and still have access to healthy food choices (specifically, supermarkets) throughout the day by their travel habits and various modes of transportation.

• Transportation options will be analyzed to evaluate their influence on the health and decisions made regarding food.

Objectives:• Identify a relationship between diet-

related disease and location of supermarkets with respect to the population

• Determine at-risk census tracts• Incorporate transit options into

findings

Methodology

• Create 3 classes of maps:– Disease Diagnosis– Transit Options– Supermarket Proximity to various transit options

• Create three indices– Transportation (subway and car)– Supermarket proximity– Diet-Related Disease Diagnosis (total DRD rates)

Combine indices into one Master Index to reveal relationships between location, mobility and health

Flow Chart1. Create .8km Polygons with

Network Dataset

2. Calculate population w/in

and outside polygons

3. Convert to percentages per

census tract

4.Map according to accessibility (not

lack of access)

Subway Access Index

1.Create .8km Polygons with

Network Dataset

2.Calculate population w/in

and outside polygons

3. Convert to percentages per

census tract

4.Map according to accessibility (not

lack of access)

1. Obtain diagnosis data from

infoshare.org

2. Join with Census tract table

3. Calculate percentage of

population w/ICD9 code

4. Sum percentages of relevant diagnosis

5. Map according to Diagnosis

1. Obtain car data from census

2.Convert to number of cars

(from households with cars)

3. Calculate percentage of

population w/car (one car per person)

4. Map according to car access per census tract

Mobility Index

Supermarket Access Index

Car Access Index

Diet-Related Disease Index

Master Index and final evaluation

Diet-Related Disease Rates Index

µ

Data Source: www.infoshare.org

Data source: www.infoshare.org

Transit Index

Source: NYC MTA developers resource

Bronx Subway AccessConvert polygons to census tract data

61% of Bronx pop. lives within .8km of a subway stop, 19.6% have access to a car**Data source: US Census Bureau

GeoProcessing the Transit Map

Original polygon sourceClipped and erased layers

Union clipped and erase layers

Dissolve census tracts to rejoin fragments

Data source: US Census Bureau

Primary Input: Access To Transportation

Bus Access – Why is it not included? [#Bus stops per census tract/(population/area)]

Homogenous distribution of bus stops per population density would of have a net effect of 0 on the mobility index.

Source data: spatiality.com, US Census Bureau

74.7% of Bronx residents live within .8km of a supermarket, 55% of subway stops have a supermarket w/in 1 block

Supermarket Access

GeoProcessing the Supermarket Index

Original polygon source“Clipped” and “Erased” layers

Clip and erase “Union” “Dissolve” census tracts to rejoin fragments

Primary Input: Supermarket Index

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Primary Input: Access To Transportation

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Primary Input: DRD Index

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Combination of Indexes • • +

- =

The Grand Finale!

Afterthought: Comparing Diagnosis and Food/Mobility to get a perspective on the accuracy of my method

References and DatasetsCensus tract, water, population, car ownership data and shapefiles obtained from: • US Census Bureau. (2008). 2008 tiger/line® shapefiles for: New York. Retrieved

from http://www2.census.gov/cgi-bin/shapefiles/state-files?state=36 Diet-Related Disease Diagnosis data obtained from:• Hospital sparks/icd-9 code data for the Bronx, NY. (2012, February 1). Retrieved

from http://www.infoshare.org Subway station point, subway line, bus station, and bus line data sets obtained from:• New York City MTA. (2012, February 1). MTA Developers Resources. Retrieved from

http://www.mta.info/developers/download.html • Romalewski, S. (2010, July 8). MTA GIS data update. Retrieved from

http://spatialityblog.com/2010/07/08/mta-gis-data-update/ Supermarket location data obtained from: GoogleEarth query (2012)