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GIS Mapping for Community Health Analysis - page 1

GIS Mapping for Community Health Analysis

May 29, 2017, Dr. Joseph Holler and Dr. Roberta Goldman

Contact email: [email protected] Website: www.josephholler.com

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Contents

Introduction to the Social Vulnerability Index ...........................................................................................................2

View a map in Indiemapper .......................................................................................................................................4

Experiment with cartographic design ........................................................................................................................6

Map the prevalence of disabled persons ...................................................................................................................8

Bivariate Mapping ................................................................................................................................................... 12

Explore additional themes ....................................................................................................................................... 14

Explore and Interpret Results .................................................................................................................................. 15

Optional: More advanced mapping ......................................................................................................................... 15

Appendix A: Geographic data sources and software .............................................................................................. 16

Appendix B: Workbook in Community Health Analysis .......................................................................................... 17

Purpose of this GIS Mapping Activity

Family medicine physicians need to know the communities they serve in order to provide the best

possible care. Fortunately, a wealth of geographic data is publicly available in the United States to help analyze

the social, economic, and environmental profile of any community. This geographic information system (GIS)

mapping activity will guide you through health indicators for Rhode Island, based on the Social Vulnerability

Index (SVI) developed by the Centers for Disease Control and Prevention (CDC). The purpose of the SVI is to

rank the vulnerability of communities, defined as the likelihood of suffering harmful health outcomes and

economic loss due to natural or human-caused disasters, including disease outbreaks. Although the CDC's focus

was on extreme events, the same variables are relevant to the ability of patients and communities to build

healthy communities and to cope with individual chronic and acute health problems.

In this exercise, you will investigate the CDC data for a census tract within the Memorial Hospital

service area and compare it to another reference location in Rhode Island or a community you are familiar

with. Then you will design thematic maps of three variables in Rhode Island: overall vulnerability, the

percentage of persons with disabilities, and a third variable of your choice. You will then interpret the patterns

and relationships between indicators and consider the implications for providing primary care in the Memorial

Hospital service are of Rhode Island.

Complete this work before your scheduled meeting with Roberta Goldman,

and bring your printed maps to that meeting.

mailto:[email protected]

http://www.josephholler.com/

http://creativecommons.org/licenses/by-nc-sa/4.0/


Introduction to the Social Vulnerability Index

Navigate the

Social

Vulnerability

Index

Go to the Social Vulnerability Index at http://svi.cdc.gov/

(this may work best in Chrome browsers) Enter the zip code of Memorial Hospital: 02860 and submit.

The interactive map will load and zoom to the 02860 zip code, outlined in blue. The

data is aggregated by census tracts, and these are outlined in light grey.

o The default view is the aggregate social vulnerability index, but you can also use the Theme drop-down menu to disaggregate the map by any of the four social vulnerability themes: 1) Socioeconomic, 2) Household Composition/Disability, 3) Minority Status/Language, or 4) Housing/Transportation.

and then

Finally, you can view all the details for a single census tract. Click on the location of Memorial Hospital to open the census tract information for

this area (tract number 016700). Follow the Social Vulnerability Profile link. This query can take a minute or two to complete.

http://svi.cdc.gov/


Social

Vulnerability

Index Data

A pop-up window will open with the full social vulnerability profile of that census

tract. Each indicator has six variables, of which the most useful ones are:

o The Number is the total number of indicated people, households, or housing units, or a rate or measure of centrality (e.g. per capita income or median household income).

o The Percentage is the ratio of indicated people, households, or housing units over the total of people, households, or housing units, expressed as a percentage.

o The Percentile Rank indicates the rank of this census tract in relation to all census tracts in the United States. A low percentile rank (0) indicates low vulnerability, while a high percentile rank (100) indicates high vulnerability. A percentile range of, e.g. 80, means that 80% of all census tracts have lower vulnerability.

o The SVI Flag will be "yes" if the indicator is of particularly high concern for social vulnerability.

Compare any census tract in Pawtucket or Central Falls with one or more census tracts you are familiar with from home or college. Fill out Appendix B: Workbook in Community Health Analysis with the statistical profile of each location (provided at the end of these instructions and as a separate Word document). Consider the following questions for discussion:

o Are the statistics for communities you know well consistent with your experience and knowledge of those communities?

o How do the statistics compare and contrast with communities in Pawtucket or Central Falls?

o For which variables do the communities rank most poorly, looking at the Percentile Ranks?

o Why do you think the CDC has used these particular indicators and how might they impact health care, both on a day-to-day basis and in disasters and emergencies?

o Note: Ranked percentiles are always given from 0 (least vulnerable) to 100 (most vulnerable). Variables with inverse relationships have already been switched for consistency. For example, the highest per capita incomes will be ranked near the 1st percentile while the highest percentages of mobile homes will be ranked near the 100th percentile.

SVI

Documentation

Full documentation of the SVI methods and indicators is available at

http://svi.cdc.gov/Documents/Data/2014_SVI_Data/SVI2014Documentation.pdf For more information about the SVI, refer to this journal article:

https://gis.cdc.gov/grasp/svi/A%20Social%20Vulnerability%20Index%20for%20Disaster%20Management.pdf

http://svi.cdc.gov/Documents/Data/2014_SVI_Data/SVI2014Documentation.pdf




View a map in Indiemapper

Why make your

own map?

The online SVI map only allows you to visualize aggregated data by percentile rank,

despite the fact that a wealth of good data has been used to compose the overall index and its four components. The SVI data has been prepared for thematic mapping in the free on-line application, indiemapper.

Launch

Indiemapper

and load the

SVI map

First, download the SVI data package for indiemapper:

http://www.josephholler.com/files/CDCSVI.imp For now, leave the file in your downloads folder without opening it.

Second, maximize your web browser. Note: Please keep your web browser maximized to the full extent of your screen while using indiemapper to avoid distorting the layout of your map.

Next, go to the indiemapper application: http://indiemapper.io/

o LAUNCH the application. o A "Your Data" window opens automatically after launching. o On the right side, go to Browse for IMP.

o Select the CDCSVI.imp file that you just downloaded above and Load it.

http://www.josephholler.com/files/CDCSVI.imp

http://indiemapper.io/


Check your

Results and

Export a Map

The default map should look like this, and represents the overall Vulnerability Index. You may need to click and drag map items in order to arrange them as seen below.

Please export an image of this social vulnerability map (for printing or importing into

Word or Powerpoint).

o Use the export button at the top right o I suggest using the JPEG file format to make it easiest to use the map in any

software program. o First Generate File and then Export to your Computer and Save.

To save a working copy of the data and your current layout (for later use in

indiemapper), use the save button:

o There is no undo feature in Indiemapper, so saving is important!


Experiment with cartographic design

Cartographic

Design

This section will guide you through changing the visibility and order, classification, and

symbology of data layers to improve the aesthetics of your map. This section is optional, so if you're short on time or have no interest in cartographic

design, skip to the Map the prevalence of disabled persons section on page 8.

Change the

Visibility and

Order of

Layers

The Layers panel, shown at right, allows you

to control which layers are visible and the order in which they are drawn.

These are aesthetic suggestions

o Check or uncheck the boxes to make layers seen or invisible.

o I suggest unchecking the Graticule layer to remove the latitude and longitude lines from the map.

o Click and drag layers under the Data Sources folder to bring layers to the foreground or background of the map.

o If you want to label towns, you may check the Name labels layer under towns.shp.

o If you want to show the inland water bodies, click and drag the water.shp layer above CDC_SVI.shp in order to draw the CDC data layer on top of the water layer.

o If you want to remove water all together, uncheck the water.shp layer.


Change the

style of a

choropleth

layer

Once you have data in Indiemapper, you have

the power to alter the symbols, classifications, and colors used to represent your data.

Select the RPL_THEMES layer and examine the style: choropleth menu beneath the Layers tab.

o A choropleth map displays numerical values by filling geographic regions with color or patterns. E.g. this map displays social vulnerability percentiles in five classes with a color gradient ranging from yellow to purple.

This menu displays a histogram of the frequency of geographic regions (in this case, census tracts) on the map.

Try altering the number of classes and the classification method.

Try changing the color scheme. For best results, avoid colors similar to the water or Memorial Hospital Service area layers.

Use the help menus for more information and best practices advice in cartography. Also see the Health Geography Primer for RI at http://www.josephholler.com/files/HealthGeogRI.pdf for more information on map classification.

After making changes to the map aesthetics, you may want to export a new map image and save your work.

http://www.josephholler.com/files/HealthGeogRI.pdf



Map the prevalence of disabled persons

Add a new data

layer to the

map to display

the percentage

of disabled

persons

Hover the mouse over the CDC_SVI.shp layer in the Layers panel.

Click the + button to the left to create a new thematic layer

A Choose a new layer to add menu appears, giving you all of the mapping options for the CDC_SVI.shp dataset. If the menu is hidden beyond the bottom of your screen, try collapsing most of the Layers panel folders before adding a new layer.

Use the following settings to create a map of disabled persons:

o Choose an attribute: EP_DISABL (not EPL_DISABL)

o Choose a map type: Choropleth o Standardize your data: No o Okay


Customize the

disabled

persons map

layer

A style: choropleth panel (shown at right)

appears after you create the layer.

o If the panel has not appeared, select the EP_DISABL layer and expand the style: choropleth menu at the bottom of the panel menus by clicking on it.

Notice the default classification method is Optimal Breaks. The data has a fairly normal distribution, and Optimal Breaks is placing a few high outlier tracts in a class of their own.

Try changing the method to Quantile. This will place an equal number of tracts in each class. Now try Equal Interval to assign equal data ranges to each class.

Which method do you think best represents the geographic pattern of disability prevalence? Set the layer to use the method of your preference. This is a subjective, aesthetic decision with no one correct answer.

Explore the

Disability

Data

If you click once on any census tract on the disability map, a pop-up window will

display the data for that census tract. E.g. clicking on Block Island reveals a 10.4 percentage of disabled persons living on the

island.

Expand the Other attributes menu to view all the social vulnerability data associated

with a census tract. Click the "x" to close the attribute information pop-up.


Update the map

elements to

match your new

data theme

Double-click the title to change "Social Vulnerability" to "Disabled Persons" Double-click the "National Percentile of Social Vulnerability by Census Tract" note and

edit the text to explain the EP_DISABL variable. In the Layers panel under the Data Sources folder, switch off the visibility of the

RPL_THEMES layer.

In the Layers panel under the Layout Objects and Legends folder, turn off visibility of

the RPL_THEMES legend. Turn on visibility of the EP_DISABL legend.

Highlight the EP_DISABL layer and expand the style: legend panel (see its heading at

the bottom of the panels). Uncheck the options for a BACKGROUND and BORDER

Click and drag the EP_DISABL legend to an appropriate position on the map. Double-click the map credits in the lower-left corner to attribute this map as your own

work.


Check your

Results and

Save

Your map should look something like the one below, depending on the classification

method and color scheme you chose.

At this point, export a JPEG of your map to save an image of it.

o See the "Export a Map" section above to remember instructions for this.

You may also want to save the map and its current layout as an indiemapper file for later use.


Bivariate Mapping

Mapping

multiple

attributes in

indiemapper

Once you create a series of single-variable maps, you may want to visualize the

relationship between two variables, and this can be done with a multivariate choropleth map. Try making a multivariate map of disabled persons and uninsured persons to identify the locations in Rhode Island with the highest rates of both.

Once again, create a new thematic layer from the CDC_SVI.shp data.

o Click the + button to the left to create a new thematic layer

This time, choose the following options:

o Multivariate layer type o Attribute 1: EP_DIABL o Attribute 2: EP_UNINSUR o Map Type: Bivariate Choropleth o Standadize your data: no for both attributes (they are already percentages)

Customize the

Bivariate

Choropleth Map

sytle

o The default style is not ideal, so try to change it by opening the style: bivariate chropleth menu (see my example at right).

o Rather than a histogram, the bivariate map menu will display a scatterplot of the data. In this case, the. In this case, the y axis is the percentage of uninsured, and the x axis is the percentage disabled.

o It's easiest to think about the relationship between two variables by visualizing them with the same measurement scale. You can do this by changing the Method to Quantile.

o Set the number of classes to 3 by 3, and select the first sequential color scheme.

Remember to format the other map elements:

o Change the title o Remove the old legend o Add the new legend and remove its

backround and border o Update the annotated text to describe

the new variables

Remember to save the indimapper file, and export an image of the map.


Interpret your

Results

In this map, black census tracks are in the top third of all Rhode Island census tracts

for highest rates of uninsurance and disability. Any White census tracks are in the bottom third for lowest rates of uninsurance and disability. Blue tracts have high rates of uninsurance and low rates of disability. Red tracts have low rates of uninsurance and high rates of disability.

For clarity, I prefer to design single-variable maps separately first, and then supplement those with a bivariate map to visualize the relationship between them.


Explore additional themes

Repeat the

process used

for the

disability map

to map a theme

of your own

interest.

Use the SVI 2014 Documentation to choose and interpret a new variable to represent

a theme of interest to you.

o The documentation is available at http://svi.cdc.gov/Documents/Data/2014_SVI_Data/SVI2014Documentation.pdf

o A graphic overview of available variables is found on page 2 of the SVI 2014 Documentation, followed by detailed explanations of each variable.

The most straightforward variables to map are percentages or percentile rankings. In the SVI data, those variables have the following prefixes:

o EPL_ indicates a percentile of all U.S. Census tracts, and should be mapped with the choropleth type. I also suggest an equal interval method to represent the data in percentiles from 0 to 20, 20 to 40, etc.

o EP_ indicates a percentage, and should be mapped with the choropleth type.

The following list includes root labels for the more interesting variables:

o Below Poverty: POV o Unemployed: UNEMP o Per Capita Income: PCI o No High School Diploma: NOHSDP o Aged 65 or Older: AGE65 o Aged 17 or Younger: AGE17 o Older than Age 5 with a Disability: DISABL o Single-Parent Households: SNGPNT o Minority: MINRTY o Speak English "Less than Well": LIMENG o Multi-Unit Structures: MUNIT o Mobile Homes: MOBILE o Crowding: CROWD o No Vehicle: NOVEH o Group Quarters: GROUPQ o Uninsured Population: UNINSUR

Deleting

Mistakes

You may want to delete mistakes along the way! If so, go to the Layers panel and click

on the unwanted layer under the Data Sources folder and click the Delete button

at the bottom of the Layers panel. Do not delete the CDC_SVI.shp layer, or you will have to reload the map.

Finalize the

Map(s)

Remember to adjust the layout of the map to match your new variable, including the

title, legend, and explanatory text annotation. Export the map as a JPEG image. Save an indiemapper file with your work.

http://svi.cdc.gov/Documents/Data/2014_SVI_Data/SVI2014Documentation.pdf


Explore and Interpret Results

Compare

multiple

variables and

look for

relationships

Open or print the images of your maps so that you can view them side-by-side.

Consider the following questions:

o Are there strong spatial patterns in the percentage of disabled persons and in the other map themes?

o Do the geographic patterns generally correlate with each other, where high values on one map correlate with high values on the other map?

o Are the patterns inversely correlated, where high values on one map almost always correlate with low values on the other map, and vis a versa?

o Are there interesting exceptions to the patterns? o How does the Memorial Hospital Service compare to other areas of the state?

Try asking local experts to help you understand the maps you've created, using the maps as a starting point for a conversation about community health in Rhode Island.

Optional: More advanced mapping

Mapping

variables

other than

percentages or

percentiles

More advanced users may also use variables with these prefixes:

o E_ indicates an estimate, and this is a total number. Only map a total number with the proportional symbol or dot density types. A total number must be standardized in order to map it with the choropleth type.

o RPL_ indicate the percentile rank of the overall vulnerability indicator or one of its four themes. It should only be mapped with the choropleth type.

Advice for map type decisions:

o If you chose a percentage, mean, median, or percentile variable, map them with the choropleth map type.

o Totals should be mapped as proportional symbols or dot density, or standardized for choropleth maps.

Advice for standardization:

o If you are mapping percentages or percentile ranks, you do not need to standardize your Data.

o If you are mapping a total number as a choropleth map, you need to standardize. This entails dividing by a second variable in order to calculate a percentage or density. For example:

o To map a percentage of total population, standardize by E_TOTPOP o To map a percentage of households, standardize by E_HH o To map a percentage of housing units, standardize by E_HU o To map a density by area, standardize by AREA_SQMI o For more discussion on standardization, see the help menu or the Health

Geography Primer for RI at http://www.josephholler.com/files/HealthGeogRI.pdf



Appendix A: Geographic data sources and software

The following resources were used to create this mapping exercise: Rhode Island Geographic Information System: http://www.rigis.org/ Centers for Disease Control and Prevention Social Vulnerability Index: http://svi.cdc.gov/ Indiemapper: http://indiemapper.com/ Some data was prepared in QGIS: http://www.qgis.org/

o For technical users: specifically, the Social Vulnerability Index data for Rhode Island was pre-processed in QGIS. The flag variables (prefix F_), error variables (prefixes M_ and MP_) and sum-of-percentile variables (prefixes SPL_) were deleted. The multipart to singleparts geometry module was used to convert the census tract geometries into a simpler form for use with indiemapper. Any exceptionally small parts resulting from geometry errors and splinters were deleted.

Other useful interactive maps for community health analysis:

The Environmental Protection Agency developed an Environmental Justice screening tool, rich with data on both social and demographic variables and environmental risks. https://www.epa.gov/ejscreen

The American Medical Association recently updated the AMA Health Workforce Mapper, which can display point locations of health providers and choropleth rates of providers per population at the county level. http://www.ama-assn.org/ama/pub/advocacy/state-advocacy-arc/health-workforce-mapper.page#free-tool

The Rhode Island Food Policy Council created an interactive Food System Map, available here: https://kkp.maps.arcgis.com/apps/webappviewer/index.html?id=357aa6baa7874466801749b7ecd402fa

Get more background and links to many more health mapping resources in the Health Geography Primer for Rhode Island Family Medicine at http://www.josephholler.com/files/HealthGeogRI.pdf

http://www.rigis.org/

http://svi.cdc.gov/

http://indiemapper.com/

http://www.qgis.org/

https://www.epa.gov/ejscreen

http://www.ama-assn.org/ama/pub/advocacy/state-advocacy-arc/health-workforce-mapper.page#free-tool

https://kkp.maps.arcgis.com/apps/webappviewer/index.html?id=357aa6baa7874466801749b7ecd402fa



Appendix B: Workbook in Community Health Analysis

Geographic Location Rhode Island Hospital Service Areaa Reference Location

State

County

Town or City

ZIP Code

Census Tract

Social Vulnerability Indicators Percent, Mean, or

Median Percentile

Rank Percent, Mean, or

Median Percentile

Rank

Poverty

Unemployment

Income

Education

Elderly

Children and Youth

Single Parent Households

Minority Race/Ethnicity

Non-English Speaking

High-density housing (>= 10 units per building)

Mobile homes

Crowded housing (more people than rooms)

No vehicle ownership

Group quarters (e.g. prisons, nursing homes,

dormitories, or barracks)

a Choose one census tract in the Rhode Island Hospital Service area, encompassing Pawtucket and Central Falls. Choose a

second census tract for a Reference Location for comparison elsewhere in Rhode Island or in a place you are familiar with.