SlideShare ist ein Scribd-Unternehmen logo
1 von 15
Downloaden Sie, um offline zu lesen
Food Deserts in South Dakota
Nimish Sheth
The Food Desert Metaphor
2
 First used in the U.K. to describe lack of access to food
due to grocery store closures in deteriorating
neighborhoods in cities
 Uneven distribution of consumer food sources leads to
areas of concentration and places with limited or non-
existent access to food choices (Morton,2005)
 Differential access to healthy and affordable food based on
socio-economic conditions (Beaulac,Kristjansson,and
Cummins,2009)
Food Desert in the U.S. context
3
 In the U.S., proliferation of convenience stores and mini-
marts provides increased access to food
 Clouds quality, nutritional, and affordability factors
 Food desert alternately defined as residential proximity to
large food retailers (Morton and Blanchard,2007)
Goals
4
 Identify and characterize food deserts in South Dakota, a
large rural state, based on geographic access to retail food
 Use GIS for identifying food deserts – regions with limited
or non-existent geographic access to large food retailers
 Create a set of maps to visualize the process of categorizing
food deserts
 Characterize food deserts vs. non-food deserts to gain socio-
economic insights, if any
Methodology
5
 Calculate distance between residential locations and
supermarkets
 Locate cities, counties, and major roads in the state to
visualize the relative locations of supermarkets and food
deserts
 Aggregate distances by census tract to identify and
characterize food deserts
Data for South Dakota
6
Data Source
Census Blocks U.S. Census Bureau
Census Tracts U.S. Census Bureau
Census Tract Demographics U.S. Census Bureau
Supermarkets (except convenience
stores)
ReferenceUSA
Roads South Dakota Dept. of
Transportation
Cities MGIS (Price), U.S. Census Bureau
State, Counties MGIS (Price)
Data Processing
7
Project Data
NAD83 SPCS
South Dakota South FIPS4002
Create GDB
Import data
Calculate Census
Block Centroids
Map Supermarkets
(lat/long)
Closest
Supermarket to
Block Centroid
Simple Distance
join
Mean Distance to
Supermarket by
Census Tract
Summarized Inside
joinCreate choropleth map
Mean Distance by Tract
Create series of
maps to visualize
analysis
Assemble Data
Analyze
characteristics of food
& non-food deserts in
ArcMap and Excel
^
Aberdeen
Brookings
Watertown
Rapid City
Sioux Falls
Pierre
South Dakota, U.S.
0 30 60 90 12015
Miles
^ Capital
Cities (2000 pop.> 5,000)
Census Tracts
Map Author: Nimish Sheth, 2009
:
8
 Large, rural Midwestern state - 75,885 sq. miles
 2000 population - 754,844; Pop. density – 9.9/sq. mile
 2000 per capita money income - $17,562
 13.2% of the population below the poverty line (poverty threshold:
1 person - $8,794; Family (3) - $13,861) From US Census Bureau
#*#*
#*
#*
#*
#*
#*
#* #*
#*
#*#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*#*#*#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*#*
#*#*#*#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*#*#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*#*#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*
#*#*#*#*
#*
#*
#*
#*
#*
#*
#*
#*#*
#*
#*
#*
#*
#*
#*
#*#*
#*
#*
#*
#* #*
#*
#*
#*
#*
#*
#*
^
Aberdeen
Brookings
Watertown
Rapid City
Sioux Falls
Pierre
Census Tracts and Supermarkets in South Dakota
0 30 60 90 12015
Miles
^ Capital
#* Supermarkets
Census Tracts
Roads
Interstate
Rural Principal Arterial
Other
Cities (2000 pop. > 5,000)
Map Author: Nimish Sheth, 2009
:
9
 66 counties
 235 census tracts
 77,951 census blocks
 144 supermarkets (NAICS code 445110 & 2,500+ sq. ft.)
10
 Closest supermarket to block centroid
 Mean distance by census tract
#*
#*
#*
!(
1.48 miles
1.52 miles
460359629001046
Walmart Supercenter
County Fair Food Store
Closest supermarket to block centroid
!( Block 460359629001046
#* Supermarkets
Roads
Interstate
Rural Principal Arterial
Other
Block Centroid
Census Tract
0 0.5 1 1.5 20.25
Miles
Map Author: Nimish Sheth, 2009
:
Average Distance to Supermarkets by Census Tract
Mean Distance to Supermarkets
by Census Tract (miles)
#* Supermarkets
0 - 1
1 - 4
4 - 8
8 - 12
> 12
0 30 60 90 12015
Miles
Map Author: Nimish Sheth, 2009
:
11
 Avg. U.S. grocery trip: 8 miles – 1995 Natl.Transportation Survey
(Morton & Blanchard,2007)
 Tracts with a mean distance > 12 miles deemed food desert
 75 of 235 tracts identified as food deserts (31.9%)
 account for 16.9% of state population
 mean distance to supermarket is 17.5 miles vs. 6.3 miles for non-food deserts
Characteristics of Food Deserts
12
Characteristic
Food Desert
Tracts
Non-Food
Desert Tracts
Median Household Income 26,156 34,600
Population 18 and over 75,321 473,450
Percent population 20 to 34 14.4 19.8
Percent population 65 and up 15.1 14.2
Percent rural population 93.7 40.4
Total Housing Units 49,109 274,099
Percentage of people with High School
diploma or more, age 25 and more
78.3 84.0
Percent disabled, 21-64 years 18.6 15.1
Percent disabled, 65 and over 39.4 39.6
Percent families in poverty 16.4 8.1
Percent individuals in poverty 22.1 11.6
Percent 65 and over in poverty 22.0 11.0
13
• Of the 20 poorest tracts (based on individual poverty rate), 15 identified as food deserts
• 5 of these 15 tracts are among the 20 tracts with the lowest educational attainment (based on
percentage of people with High School diploma or more)
• Of the 20 tracts with the lowest educational attainment, 14 identified as food deserts
• Of the 20 food deserts with the greatest distance from supermarkets:
• 4 are among the top 20 tracts with greatest rate of individual poverty
• 3 are among the top 20 tracts with the least educational attainment
• 2 are among the top 20 tracts with the least median household Income
!(
!(
!(
!(
!( !( !(
!( !( !(
!(
!(!(
!(
!(
^
Pierre
Aberdeen
Brookings
Watertown
Rapid City
Sioux Falls
Food Desert Categorization of CensusTracts
0 30 60 90 12015
Miles
^ Capital
!( Cities (2000 pop. > 5,000)
Counties
Food Desert Census Tract
Non-Food Desert Census Tract
Map Author: Nimish Sheth, 2009
:
Limitations and Future Research
14
 Block centroids are a gross approximation of residential
locations
 Euclidean distance not reflective of true travel distance
 Residents not constrained by state boundaries
 Home/community gardens, farmers’ markets, etc. not
considered
 Economic and Informational food access
References
15
 U.S. Census Bureau
 ReferenceUSA
 South Dakota Dept. ofTransportation
 Price, M. Mastering ArcGIS, 4th Edition (Exercise Data)
 Morton, L.W. and Blanchard,T.C. (2007). “Starved for Access:
Life in Rural America’s Food Deserts.” Rural Realities 1 (4): 1-10.
 Morton, L.W. et al., (2005). “Solving the Problems of Iowa Food
Deserts: Food Insecurity and Perceptions of Civic Structure.”
Rural Sociology 70 (1): 94-112.

Weitere ähnliche Inhalte

Ähnlich wie Food deserts in South Dakota

Addressing Built Environmental Justice
Addressing Built Environmental JusticeAddressing Built Environmental Justice
Addressing Built Environmental Justice
Mary Black
 
Housing Virginia Rural Report - Nov 2016
Housing Virginia Rural Report - Nov 2016Housing Virginia Rural Report - Nov 2016
Housing Virginia Rural Report - Nov 2016
Alise Newman
 
Godsil Obesity and BE Poster logtransformed 2
Godsil Obesity and BE Poster logtransformed 2Godsil Obesity and BE Poster logtransformed 2
Godsil Obesity and BE Poster logtransformed 2
Olivia Godsil
 
Wide Open Spaces: Schooling in Rural America Today
Wide Open Spaces: Schooling in Rural America TodayWide Open Spaces: Schooling in Rural America Today
Wide Open Spaces: Schooling in Rural America Today
Jeremy Knight
 

Ähnlich wie Food deserts in South Dakota (20)

Data for Decision Maker
Data for Decision MakerData for Decision Maker
Data for Decision Maker
 
Addressing Built Environmental Justice
Addressing Built Environmental JusticeAddressing Built Environmental Justice
Addressing Built Environmental Justice
 
First Publication Gis Korea Markc
First Publication Gis Korea MarkcFirst Publication Gis Korea Markc
First Publication Gis Korea Markc
 
Minnick finalposter
Minnick finalposterMinnick finalposter
Minnick finalposter
 
Unpacking the 2010 Census - Part 1
Unpacking the 2010 Census - Part 1Unpacking the 2010 Census - Part 1
Unpacking the 2010 Census - Part 1
 
Housing Virginia Rural Report - Nov 2016
Housing Virginia Rural Report - Nov 2016Housing Virginia Rural Report - Nov 2016
Housing Virginia Rural Report - Nov 2016
 
Miad Food Web Presentation
Miad Food Web PresentationMiad Food Web Presentation
Miad Food Web Presentation
 
Walsack, Phil, MPUA, Baseline Statistics Demographic Trends State of the Stat...
Walsack, Phil, MPUA, Baseline Statistics Demographic Trends State of the Stat...Walsack, Phil, MPUA, Baseline Statistics Demographic Trends State of the Stat...
Walsack, Phil, MPUA, Baseline Statistics Demographic Trends State of the Stat...
 
Godsil Obesity and BE Poster logtransformed 2
Godsil Obesity and BE Poster logtransformed 2Godsil Obesity and BE Poster logtransformed 2
Godsil Obesity and BE Poster logtransformed 2
 
9th International Public Markets Conference - Larrry Lund
9th International Public Markets Conference - Larrry Lund9th International Public Markets Conference - Larrry Lund
9th International Public Markets Conference - Larrry Lund
 
Transportation and Food: The Importance of Access
Transportation and Food: The Importance of AccessTransportation and Food: The Importance of Access
Transportation and Food: The Importance of Access
 
Exploring Dallas Poverty in Local, Regional, and National Contexts
Exploring Dallas Poverty in Local, Regional, and National ContextsExploring Dallas Poverty in Local, Regional, and National Contexts
Exploring Dallas Poverty in Local, Regional, and National Contexts
 
B8 utilize data to advocate tim parker- usda ers
B8 utilize data to advocate   tim parker- usda ersB8 utilize data to advocate   tim parker- usda ers
B8 utilize data to advocate tim parker- usda ers
 
TBR Food Access #1: What's a food desert? Where are they in Baton Rouge?
TBR Food Access #1: What's a food desert? Where are they in Baton Rouge?TBR Food Access #1: What's a food desert? Where are they in Baton Rouge?
TBR Food Access #1: What's a food desert? Where are they in Baton Rouge?
 
Suburbanization of Poverty in Metro Atlanta: An Update
Suburbanization of Poverty in Metro Atlanta: An UpdateSuburbanization of Poverty in Metro Atlanta: An Update
Suburbanization of Poverty in Metro Atlanta: An Update
 
US consumer trends report
US consumer trends reportUS consumer trends report
US consumer trends report
 
US Consumer trends report 2017
US Consumer trends report 2017US Consumer trends report 2017
US Consumer trends report 2017
 
2017 us-trends-full-report
2017 us-trends-full-report2017 us-trends-full-report
2017 us-trends-full-report
 
US Consumer Trends Report
US Consumer Trends ReportUS Consumer Trends Report
US Consumer Trends Report
 
Wide Open Spaces: Schooling in Rural America Today
Wide Open Spaces: Schooling in Rural America TodayWide Open Spaces: Schooling in Rural America Today
Wide Open Spaces: Schooling in Rural America Today
 

Kürzlich hochgeladen

Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
HyderabadDolls
 
Gartner's Data Analytics Maturity Model.pptx
Gartner's Data Analytics Maturity Model.pptxGartner's Data Analytics Maturity Model.pptx
Gartner's Data Analytics Maturity Model.pptx
chadhar227
 
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
nirzagarg
 
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
nirzagarg
 
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
gajnagarg
 
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
nirzagarg
 
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
gajnagarg
 
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
HyderabadDolls
 
Lecture_2_Deep_Learning_Overview-newone1
Lecture_2_Deep_Learning_Overview-newone1Lecture_2_Deep_Learning_Overview-newone1
Lecture_2_Deep_Learning_Overview-newone1
ranjankumarbehera14
 

Kürzlich hochgeladen (20)

Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
Sonagachi * best call girls in Kolkata | ₹,9500 Pay Cash 8005736733 Free Home...
 
Nirala Nagar / Cheap Call Girls In Lucknow Phone No 9548273370 Elite Escort S...
Nirala Nagar / Cheap Call Girls In Lucknow Phone No 9548273370 Elite Escort S...Nirala Nagar / Cheap Call Girls In Lucknow Phone No 9548273370 Elite Escort S...
Nirala Nagar / Cheap Call Girls In Lucknow Phone No 9548273370 Elite Escort S...
 
Gartner's Data Analytics Maturity Model.pptx
Gartner's Data Analytics Maturity Model.pptxGartner's Data Analytics Maturity Model.pptx
Gartner's Data Analytics Maturity Model.pptx
 
Vadodara 💋 Call Girl 7737669865 Call Girls in Vadodara Escort service book now
Vadodara 💋 Call Girl 7737669865 Call Girls in Vadodara Escort service book nowVadodara 💋 Call Girl 7737669865 Call Girls in Vadodara Escort service book now
Vadodara 💋 Call Girl 7737669865 Call Girls in Vadodara Escort service book now
 
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Tumkur [ 7014168258 ] Call Me For Genuine Models We...
 
High Profile Call Girls Service in Jalore { 9332606886 } VVIP NISHA Call Girl...
High Profile Call Girls Service in Jalore { 9332606886 } VVIP NISHA Call Girl...High Profile Call Girls Service in Jalore { 9332606886 } VVIP NISHA Call Girl...
High Profile Call Girls Service in Jalore { 9332606886 } VVIP NISHA Call Girl...
 
Gulbai Tekra * Cheap Call Girls In Ahmedabad Phone No 8005736733 Elite Escort...
Gulbai Tekra * Cheap Call Girls In Ahmedabad Phone No 8005736733 Elite Escort...Gulbai Tekra * Cheap Call Girls In Ahmedabad Phone No 8005736733 Elite Escort...
Gulbai Tekra * Cheap Call Girls In Ahmedabad Phone No 8005736733 Elite Escort...
 
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
 
Digital Transformation Playbook by Graham Ware
Digital Transformation Playbook by Graham WareDigital Transformation Playbook by Graham Ware
Digital Transformation Playbook by Graham Ware
 
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
Top profile Call Girls In Bihar Sharif [ 7014168258 ] Call Me For Genuine Mod...
 
Kings of Saudi Arabia, information about them
Kings of Saudi Arabia, information about themKings of Saudi Arabia, information about them
Kings of Saudi Arabia, information about them
 
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
Top profile Call Girls In Chandrapur [ 7014168258 ] Call Me For Genuine Model...
 
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
Top profile Call Girls In Satna [ 7014168258 ] Call Me For Genuine Models We ...
 
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
Top profile Call Girls In Indore [ 7014168258 ] Call Me For Genuine Models We...
 
SAC 25 Final National, Regional & Local Angel Group Investing Insights 2024 0...
SAC 25 Final National, Regional & Local Angel Group Investing Insights 2024 0...SAC 25 Final National, Regional & Local Angel Group Investing Insights 2024 0...
SAC 25 Final National, Regional & Local Angel Group Investing Insights 2024 0...
 
7. Epi of Chronic respiratory diseases.ppt
7. Epi of Chronic respiratory diseases.ppt7. Epi of Chronic respiratory diseases.ppt
7. Epi of Chronic respiratory diseases.ppt
 
Gomti Nagar & best call girls in Lucknow | 9548273370 Independent Escorts & D...
Gomti Nagar & best call girls in Lucknow | 9548273370 Independent Escorts & D...Gomti Nagar & best call girls in Lucknow | 9548273370 Independent Escorts & D...
Gomti Nagar & best call girls in Lucknow | 9548273370 Independent Escorts & D...
 
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
Sealdah % High Class Call Girls Kolkata - 450+ Call Girl Cash Payment 8005736...
 
Lecture_2_Deep_Learning_Overview-newone1
Lecture_2_Deep_Learning_Overview-newone1Lecture_2_Deep_Learning_Overview-newone1
Lecture_2_Deep_Learning_Overview-newone1
 
Discover Why Less is More in B2B Research
Discover Why Less is More in B2B ResearchDiscover Why Less is More in B2B Research
Discover Why Less is More in B2B Research
 

Food deserts in South Dakota

  • 1. Food Deserts in South Dakota Nimish Sheth
  • 2. The Food Desert Metaphor 2  First used in the U.K. to describe lack of access to food due to grocery store closures in deteriorating neighborhoods in cities  Uneven distribution of consumer food sources leads to areas of concentration and places with limited or non- existent access to food choices (Morton,2005)  Differential access to healthy and affordable food based on socio-economic conditions (Beaulac,Kristjansson,and Cummins,2009)
  • 3. Food Desert in the U.S. context 3  In the U.S., proliferation of convenience stores and mini- marts provides increased access to food  Clouds quality, nutritional, and affordability factors  Food desert alternately defined as residential proximity to large food retailers (Morton and Blanchard,2007)
  • 4. Goals 4  Identify and characterize food deserts in South Dakota, a large rural state, based on geographic access to retail food  Use GIS for identifying food deserts – regions with limited or non-existent geographic access to large food retailers  Create a set of maps to visualize the process of categorizing food deserts  Characterize food deserts vs. non-food deserts to gain socio- economic insights, if any
  • 5. Methodology 5  Calculate distance between residential locations and supermarkets  Locate cities, counties, and major roads in the state to visualize the relative locations of supermarkets and food deserts  Aggregate distances by census tract to identify and characterize food deserts
  • 6. Data for South Dakota 6 Data Source Census Blocks U.S. Census Bureau Census Tracts U.S. Census Bureau Census Tract Demographics U.S. Census Bureau Supermarkets (except convenience stores) ReferenceUSA Roads South Dakota Dept. of Transportation Cities MGIS (Price), U.S. Census Bureau State, Counties MGIS (Price)
  • 7. Data Processing 7 Project Data NAD83 SPCS South Dakota South FIPS4002 Create GDB Import data Calculate Census Block Centroids Map Supermarkets (lat/long) Closest Supermarket to Block Centroid Simple Distance join Mean Distance to Supermarket by Census Tract Summarized Inside joinCreate choropleth map Mean Distance by Tract Create series of maps to visualize analysis Assemble Data Analyze characteristics of food & non-food deserts in ArcMap and Excel
  • 8. ^ Aberdeen Brookings Watertown Rapid City Sioux Falls Pierre South Dakota, U.S. 0 30 60 90 12015 Miles ^ Capital Cities (2000 pop.> 5,000) Census Tracts Map Author: Nimish Sheth, 2009 : 8  Large, rural Midwestern state - 75,885 sq. miles  2000 population - 754,844; Pop. density – 9.9/sq. mile  2000 per capita money income - $17,562  13.2% of the population below the poverty line (poverty threshold: 1 person - $8,794; Family (3) - $13,861) From US Census Bureau
  • 9. #*#* #* #* #* #* #* #* #* #* #*#* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #*#*#*#* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #*#* #*#*#*#* #* #* #* #* #* #* #* #* #* #* #* #* #* #*#*#* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #*#*#* #* #* #* #* #* #* #* #* #* #* #* #* #*#*#*#* #* #* #* #* #* #* #* #*#* #* #* #* #* #* #* #*#* #* #* #* #* #* #* #* #* #* #* #* ^ Aberdeen Brookings Watertown Rapid City Sioux Falls Pierre Census Tracts and Supermarkets in South Dakota 0 30 60 90 12015 Miles ^ Capital #* Supermarkets Census Tracts Roads Interstate Rural Principal Arterial Other Cities (2000 pop. > 5,000) Map Author: Nimish Sheth, 2009 : 9  66 counties  235 census tracts  77,951 census blocks  144 supermarkets (NAICS code 445110 & 2,500+ sq. ft.)
  • 10. 10  Closest supermarket to block centroid  Mean distance by census tract #* #* #* !( 1.48 miles 1.52 miles 460359629001046 Walmart Supercenter County Fair Food Store Closest supermarket to block centroid !( Block 460359629001046 #* Supermarkets Roads Interstate Rural Principal Arterial Other Block Centroid Census Tract 0 0.5 1 1.5 20.25 Miles Map Author: Nimish Sheth, 2009 :
  • 11. Average Distance to Supermarkets by Census Tract Mean Distance to Supermarkets by Census Tract (miles) #* Supermarkets 0 - 1 1 - 4 4 - 8 8 - 12 > 12 0 30 60 90 12015 Miles Map Author: Nimish Sheth, 2009 : 11  Avg. U.S. grocery trip: 8 miles – 1995 Natl.Transportation Survey (Morton & Blanchard,2007)  Tracts with a mean distance > 12 miles deemed food desert  75 of 235 tracts identified as food deserts (31.9%)  account for 16.9% of state population  mean distance to supermarket is 17.5 miles vs. 6.3 miles for non-food deserts
  • 12. Characteristics of Food Deserts 12 Characteristic Food Desert Tracts Non-Food Desert Tracts Median Household Income 26,156 34,600 Population 18 and over 75,321 473,450 Percent population 20 to 34 14.4 19.8 Percent population 65 and up 15.1 14.2 Percent rural population 93.7 40.4 Total Housing Units 49,109 274,099 Percentage of people with High School diploma or more, age 25 and more 78.3 84.0 Percent disabled, 21-64 years 18.6 15.1 Percent disabled, 65 and over 39.4 39.6 Percent families in poverty 16.4 8.1 Percent individuals in poverty 22.1 11.6 Percent 65 and over in poverty 22.0 11.0
  • 13. 13 • Of the 20 poorest tracts (based on individual poverty rate), 15 identified as food deserts • 5 of these 15 tracts are among the 20 tracts with the lowest educational attainment (based on percentage of people with High School diploma or more) • Of the 20 tracts with the lowest educational attainment, 14 identified as food deserts • Of the 20 food deserts with the greatest distance from supermarkets: • 4 are among the top 20 tracts with greatest rate of individual poverty • 3 are among the top 20 tracts with the least educational attainment • 2 are among the top 20 tracts with the least median household Income !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( ^ Pierre Aberdeen Brookings Watertown Rapid City Sioux Falls Food Desert Categorization of CensusTracts 0 30 60 90 12015 Miles ^ Capital !( Cities (2000 pop. > 5,000) Counties Food Desert Census Tract Non-Food Desert Census Tract Map Author: Nimish Sheth, 2009 :
  • 14. Limitations and Future Research 14  Block centroids are a gross approximation of residential locations  Euclidean distance not reflective of true travel distance  Residents not constrained by state boundaries  Home/community gardens, farmers’ markets, etc. not considered  Economic and Informational food access
  • 15. References 15  U.S. Census Bureau  ReferenceUSA  South Dakota Dept. ofTransportation  Price, M. Mastering ArcGIS, 4th Edition (Exercise Data)  Morton, L.W. and Blanchard,T.C. (2007). “Starved for Access: Life in Rural America’s Food Deserts.” Rural Realities 1 (4): 1-10.  Morton, L.W. et al., (2005). “Solving the Problems of Iowa Food Deserts: Food Insecurity and Perceptions of Civic Structure.” Rural Sociology 70 (1): 94-112.