Community Opportunity Index

coi

                   Figure: Community opportunity index in Columbus, Ohio

INTRODUCTION

Geographical mapping of community opportunity can help identify social inequity, using a spatially aggregated index comprised of a set of socioeconomic factors. This idea is based on the concept of “neighborhood effects” that where people live influences their socioeconomic outcomes (Acevedo‐Garcia et al., 2004; Jencks and Mayer, 1990). A community opportunity index (COI) can be computed by combining a set of un-weighted standardized neighborhood factors and mapped by using GIS. Wang and Chen (2017) applied this approach to compute a COI for visualizing, identifying, and analyzing the spatial opportunity and deprivation in Columbus, Ohio.

METHOD

In order to create a community opportunity index (COI), physical and socioeconomic data were collected to evaluate the community performance for the neighborhoods in Columbus, Ohio. Census tract data were used as the neighborhood proxies. The following table shows the descriptive statistics of the composite variables in four categories, including economic opportunity, education and child-wellbeing, housing and neighborhood quality, and mobility and accessibility. Data sources include the estimates in 2006-2010 American Community Survey (ACS), the General Transit Feed Specification (GTFS) database, Ohio School Report Cards, the 2010 Census Summary File 1, and Census Transportation Planning Products (CTPP). There are two steps to construct the COI. First, a set of Z-scores are calculated for each tract by standardizing the factors reported in the Table. Secondly, these Z-scores are combined in equal weight to be the COI. Z-Scores for negative factors were multiplied by −1 to create composite scores that represent low-to-high opportunity. A tract with a positive score tends to have a better opportunity, and vice versa.

RESULTS

The spatial distribution of the computed COI, together with main roads, hospitals, schools, and libraries, is illustrated in the Figure below. Several spatial clusters with high COI scores are located in the north, such as Upper Arlington, Worthington, Dublin, and New Albany. In the meantime, vulnerable communities mostly cluster around the city center and in the south. In addition, an ArcGIS shapefile of the COI outcomes can be downloaded using the following link.

Table: Definition and descriptive statistics of community opportunity composite variables

Variable

Definitions

Mean

S.D.

Opportunity Index

COI

Community opportunity index (Z-score)

0.00000

9.58

Economic Opportunity

INCO

Median household income ($)

50,014

2,6385

UEMP

Unemployment rate (%)

10.10

9.36

PBAS

Households with public assistance income

44.18

43.23

POVE

Total persons below the poverty line (%)

20.63

18.28

JCHA

Percentage change of jobs from 2005 to 2010 (%)

-0.40

39.90

TACJ

Jobs reached within a 30-min transit commuting buffer

16,892

29,578

CACJ

Jobs reached within a 15-min driving buffer

328,606

117,903

Education & Child-Wellbeing

AEDE

Population with at least a bachelor's degree

1,596

1,151

SPOV

Student poverty rate (%)

25.16

24.16

PSRT

Percentage of students who are proficient at reading (%)

74.90

11.49

PSMT

Percentage of students who are proficient at math (%)

68.53

13.72

DROP

Dropout rate (%)

6.05

10.15

EXPE

Expenditure per pupil ($)

12855.11

1603.23

STRA

Student teacher ratio (%)

15.60

0.98

TQUA

Full-time teachers

33.35

41.02

GRAD

High school graduation rate (%)

85.22

7.87

Neighborhood & Housing Quality

HVAL

Median value of owner-occupied housing units ($)

152,537

82,712

VACA

Housing vacancy rate (%)

10.31

7.92

CRIM

Number of adult residents admitted to prison per 1000 people

3.76

3.99

HOWN

Home ownership rate (%)

48.77

23.99

PCHA

Change rate of estimated population from 2005 to 2010 (%)

4.55

14.28

Mobility & Accessibility

CTIM

Mean travel time to work (minute)

26.59

9.87

DHOS

Distance to nearest hospital (mile)

2.56

1.63

DSCH

Distance to nearest school (mile)

0.47

0.38

DROD

Distance to nearest primary and secondary road (mile)

0.55

0.43

DBUS

Distance to nearest bus stop (mile)

0.42

0.57

Number of observations: 284 

REFERENCES

  1. Acevedo‐Garcia, D., Osypuk, T.L., Werbel, R.E., Meara, E.R., Cutler, D.M., Berkman, L.F., 2004. Does housing mobility policy improve health? Housing Policy Debate 15, 49-98.
  2. Jencks, C., Mayer, S.E., 1990. The social consequences of growing up in a poor neighborhood. Inner-city poverty in the United States 111, 186.
  3. Wang, C-H. and Chen, N.,2017. A geographically weighted regression approach to investigating the spatially varied built-environment effects on community opportunity. Journal of Transport Geography 62, 136-147.