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![Page 1: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/1.jpg)
The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention:
The Case of Tobacco
Indiana Prevention Resource CenterBarbara Seitz de Martinez, PhD, MLS, CPP
Ruth Gassman, PhDDesiree Goetze, MPH
National Prevention Network Annual Conference
Lexington, KentuckyAugust 28, 2006
![Page 2: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/2.jpg)
What You Will Learn:
• Components of GIS system and costs• How GIS Can Help You with Program Planning
– Obtain Demographic Background– Profile Needs, Resources– Locate Problem Area or Target Audience– Inform Decisions about Strategy Selection– Enhance Cultural Competency– Obtain Funding
• How GIS Can Help You with Program Evaluation– Create a Risk/Protection Surveillance System– Track Change
• How GIS Can Help You Do Research– Conduct Research to identify relationships among
environmental and health variables
![Page 3: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/3.jpg)
I. Components of a GIS System
Minimal Equipment and
Personnel Skill Requirements
![Page 4: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/4.jpg)
Stages for Data Import/Analysis
Stage 3: Complex data import & analyze
Stage 2: Simple data imports & analysis
Stage 1: Extract data
![Page 5: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/5.jpg)
Stage One
Objective: GIS to Inform Program Planning– Identify Problem Area or Find Target Audience– Obtain Demographic Background– Inform Decisions about Strategy Selection– Enhance Cultural Competency
Equipment: Computer Hardware and Software – Standard Desktop/Laptop and Printer– GIS software: MapInfo and PCensus for MapInfo. Or
ArcView equivalentData: Purchased Databases
– AGS Core Demographics, Consumer Spending, and MRI Lifestyle Variables or Claritas Equivalent
Kinds of Skills (Capacity Building)– Computer Literacy and Intro to Microsoft Excel
![Page 6: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/6.jpg)
Levels of Software Tools
MapInfo, PCensus, Maploader
(1)
![Page 7: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/7.jpg)
Levels of Data Complexity
Purchased GIS data
(1)
![Page 8: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/8.jpg)
Examples of Data
AGS, Claritas™Map files
(1)
![Page 9: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/9.jpg)
Levels of Skill Complexity
Basic ComputerAnd Printer
(1)
![Page 10: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/10.jpg)
Stage Two
Objectives: GIS to Monitor Program Effectiveness– Create a Risk/Protection Surveillance System– Track Change
Additional Equipment: Geocoding Software – MapMarker Geocoding Software– Color Printer
Additional Data: – Local program and local geographic location data to be
imported
Additional Skills (Capacity Building)– Patience and precision– Microsoft Excel and some Microsoft Access preferable
![Page 11: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/11.jpg)
Levels of Software Required
MapInfo, PCensus, Maploader
(1)
Mapmarker Geocoding software, Excel & Access
(2)
![Page 12: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/12.jpg)
Levels of Data Complexity
Purchased GIS data
(1)
Imported data (free or purchased)
(2)
![Page 13: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/13.jpg)
Examples of Data
AGS, Claritas™,Map files
(1)
Program Data, Address Data, Health Data (public
or purchased)(2)
![Page 14: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/14.jpg)
Levels of Skills Required
Basic Computer(1)
Geocoding, Excel and Access
(2)
![Page 15: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/15.jpg)
Stage Three
Objectives: GIS to Support Research– to study relationships among environmental and health
variables
Additional Equipment: Geocoding Software – SPSS Software
Additional Data (to be imported): – Local data– Public data– Purchased data
Additional Skills (Capacity Building)– Excellent Microsoft Excel and Access skills– Excellent statistical analysis and SPSS skills
![Page 16: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/16.jpg)
Levels of Software Required
MapInfo, PCensus, Maploader
(1)
Mapmarker Geocoding software, Excel & Access
(2)
SPSS (3)
![Page 17: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/17.jpg)
Levels of Data Complexity
Purchased GIS data
(1)
Imported data (free or purchased)
(2)
More complex imported data(free or purchased)
(3)
![Page 18: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/18.jpg)
Examples of Data
AGS, Claritas™(1)
Program Data, Address Data, Health Data (public
or purchased)(2)
Mortality Report Data Morbidity Data
(public or purchased) (3)
![Page 19: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/19.jpg)
Levels of Skill Complexity
Basic Computer(1)
Geocoding, Excel and Access
(2)
Excel, Access, SPSS(3)
![Page 20: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/20.jpg)
Examples of Data
• AGS Core Demographics from Tetrad• Program Enrollment/Completion Numbers• Pre and Post- Test Scores• Addresses (e.g., of programs, outlets, agencies)• Data that needs cleaning, linking, reordering (e.g.,
Health Department Reports • Data that involves coding, joins, restructuring (e.g.,
Religent Planning 2 Morbidity Data• Data from analyses involving statistical calculations
(e.g., importing data results from your analysis for mapping)
![Page 21: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/21.jpg)
II. How GIS Can Help You with Program Planning
Obtain Demographic BackgroundProfile Needs, Resources
Locate Problem Area or Target AudienceInform Decisions about Strategy Selection
Enhance Cultural CompetencyObtain Funding
![Page 22: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/22.jpg)
Examples of Demographics
• Population• Age• Race/Ethnicity• Marital Status• Income• Occupation• Health Insurance Status• Health Status• Behaviors: Spending, Drug Use• Behaviors: Crime
![Page 23: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/23.jpg)
Forest Manor / Martindale-Brightwood Neighborhoods
The Place: Neighborhood
![Page 24: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/24.jpg)
[ Children in Poverty ] / [ Total Children ]
Locate Problem Area: Child Poverty
AG
S Indiana C
ore D
emographics
![Page 25: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/25.jpg)
AG
S Indiana C
ore D
emographics
Locate Target Audience
Where are the 10-14 year olds in Marion County?
They are in the areas that are darkest green.
![Page 26: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/26.jpg)
AG
S Indiana C
ore D
emographics
Study a Place
![Page 27: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/27.jpg)
46218
AG
S Indiana C
ore D
emographics
The Place: Government Boundaries
![Page 28: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/28.jpg)
AG
S Indiana C
ore D
emographics
Risk/Protective Factors
AG
S Indiana C
ore D
emographics
![Page 29: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/29.jpg)
Education, Less Than HS Diploma
AGS, Core Demographics,2004 est., 2005
Indiana Prevention Resource Center
Source: GIS in Prevention, County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 30: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/30.jpg)
By Census Tract and w/in a 1 Mile Radius of John Marshall Middle School
Data for addresses of retail tobacco outlets were contributed bythe Indiana State Excise Police TRIP Inspection Program.
Less Than 9th Grade Education
![Page 31: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/31.jpg)
Insurance Coverage
Insurance Coverage
AG
S Indiana C
ore Dem
ographics, 2002 est.
![Page 32: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/32.jpg)
Insurance Coverage
Source: MRI Consumer Behavior
![Page 33: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/33.jpg)
Single-Parent Families (#)
492
180
418
212
303
226
212
AG
S Indiana C
ore D
emographics
![Page 34: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/34.jpg)
Combined Indicators: Single-Parent Families & Poverty
Number of Single Parent-Families in Poverty in Each Block Group in Blue Box
AG
S Indiana C
ore D
emographics
![Page 35: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/35.jpg)
Working Parents
Children Aged 6-17 Living with…
MarionCounty
Forest Manor/ Brtwd-Mrtndle Neighborhood
# % # %
Two parents who work 57,972 43 383 11
One parent who works 4,1001 30 1,998 55
Source: U.S. Census 2000, SF3
![Page 36: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/36.jpg)
AGS Indiana, Crime Risk
Personal Crime Indices
MarionCounty
Forest Manor/ Brtwd-Mrtndle Neighborhood
Total Crime Index 202 283
Personal Crime Index 221 275
Murder 255 178
Rape 222 234
Robbery 223 356
Assault 185 328
![Page 37: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/37.jpg)
AGS Indiana, Crime Risk 2002 (2003)
Property Crime Indices
Marion County
Forest Manor/ Brtwd-Mrtndle Neighborhood
Total Crime Index 202 283
Property Crime Index 183 291
Burglary 183 297
Larceny 148 273
Car Theft 218 302
![Page 38: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/38.jpg)
AGS MRI Consumer Behavior 2002 (2003)
Voting and Volunteerism
Marion County
Forest Manor/ Brtwd-Mrtndle Neighborhood
In the Last Year, Percentage of Adults Who…
Voted in Federal, Stateor Local Election 44.0 33.0
Actively worked
as a Volunteer 16.8 10.0
![Page 39: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/39.jpg)
Income
See Relationships between Data
10-17 Year Olds
![Page 40: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/40.jpg)
6.6 Household Spending on Alcohol
Table 6.6: Per Household Spending on Alcohol (AGS, Consumer Spending, 2004, 2005)
Per Household Spending on Alcohol, 2004 est. (AGS, 2005)
Hamilton Indiana U.S.
Consumer spending on alcoholic beverages 646 439 460
Spending on Alcohol for Consumption outside the Home 279 188 197
Beer and ale away from home 92 62 65
Wine away from home 43 29 30
Whiskey away from home 72 48 50
Alcohol On Out-Of-Town Trips 72 49 52
Spending on Alcohol for Consumption in the Home 366 250 261
Beer and ale at home 211 145 152
Wine at home 89 60 63
Whiskey and other liquor at home 66 45 46
Source: GIS in Prevention, Hamilton County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 41: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/41.jpg)
Spending on Beer/Ale for Home
AGS, Consumer Spending,2004 est., 2005
Indiana Prevention Resource Center
Source: GIS in Prevention, Hamilton County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 42: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/42.jpg)
6.7 Household Spending on Tobacco
Table 6.7: Per Household Spending on Tobacco Products, Miscellaneous Reading and Personal Insurance (AGS, Consumer Spending, 2004, 2005)
Per Household Spending on Tobacco, 2004, est. (AGS, 2005)
Morgan Indiana U.S.
Per Household Spending on Tobacco Products 448 428 443
Cigarettes 405 388 400
Other Tobacco Products 43 41 44
Per Household Spending on Misc. Reading 254 245 257
Newspapers 113 109 114
Magazines 54 52 54
Books 87 84 88
Personal insurance 547 523 552
Source: GIS in Prevention, Morgan County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 43: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/43.jpg)
Race, Black
Source: GIS in Prevention, County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 44: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/44.jpg)
Race, Black
Source: GIS in Prevention, Dubois County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 45: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/45.jpg)
Ethnicity, Hispanic/Latino
Source: GIS in Prevention, County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 46: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/46.jpg)
Ethnicity, Hispanic/Latino
Source: GIS in Prevention, Dubois County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 47: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/47.jpg)
Ethnicity: Hispanic/Latino
Source: GIS in Prevention, County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
![Page 48: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/48.jpg)
Inform Decision about Strategy
• Which Curricula? For whom? Which problem?• Which Domain to focus on? Parent? Child?• Which Communication Strategy to use? Words or
pictures? Phone Calls? Literacy level?• Where to Focus your efforts? Program location?• What Criteria to apply? Poverty? Working
parents? • What Services to offer? Transportation? Food? • Extend of Need? Limit or expand service area?
![Page 49: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/49.jpg)
Stage Two Enhancements
Importing Local Data
Geocoding
Percentages, Rates and Rankings
Analysis and Custom Mapping
![Page 50: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/50.jpg)
Stage Two:Importing Local Data
Methamphetamine Lab Seizures
![Page 51: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/51.jpg)
Imported Data:Meth Busts, 2005
Total lab busts to mid October, 846 Indiana Prevention Resource Center
Source: IN State Police, 2005
![Page 52: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/52.jpg)
Stage Two:Geocoding Program Locations
and Studying Risk/Protective Factors
ARII Location Relative to
Persons in Poverty and
Families in Poverty
![Page 53: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/53.jpg)
Geocoding ofAfternoons R.O.C.K. in Indiana Programs
![Page 54: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/54.jpg)
Afternoons Rock in IN Programs
Fort Wayne, Indiana
![Page 55: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/55.jpg)
Persons Living in Poverty (Percent)Fort Wayne city, IN, by BG
Over 25%
14 to 25%
7 to 14%
4 to 7%
0 to 4 %
Persons in Poverty and Program Placement
Fort Wayne, Indiana
![Page 56: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/56.jpg)
Fort Wayne, Indiana
Families in Poverty and Program Placement
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Numbered Block Groups Have Over 50% of Families w/ Children under 18 Living in Poverty
Fort Wayne, Indiana
![Page 58: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/58.jpg)
Stage Two:Enhanced Analysisfor Risk/Protection
Adding Percentages, Rates and Rankings
![Page 59: The Potential of Geographic Information Systems to Facilitate Data-Driven Prevention: The Case of Tobacco Indiana Prevention Resource Center Barbara Seitz.](https://reader035.fdocuments.in/reader035/viewer/2022062716/56649dca5503460f94ac1153/html5/thumbnails/59.jpg)
5.7 Educational Attainment
Table 5.7: Educational Attainment (AGS, 2004 est., 2005)
Educational Attainment (%), 2004 est. (AGS, 2005)
Dubois Co. Indiana U.S.
Less than 9th grade 9.1 5.3 7.6
9th to 12th grade, no diploma 10.8 12.6 12
Total, Less Than 9th or Less Than HS Diploma 19.9 17.8 19.6
High school graduate 44.7 37.2 28.6
Some college, no degree 13.9 19.8 21.1
Associate degree 7.4 5.8 6.3
Bachelor's degree 9.2 12.2 15.6
Graduate or profession degree 4.9 7.2 8.9
Rank for % of Pop 25+ w/ less than HS diploma 39 26th of 51
Rank for % of Pop 25+ w/ a college degree 22 43rd of 51
Source: GIS in Prevention, Dubois County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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5.8 Households (Families, w/ Child, Income)
Table 5.8: Median Age and Household Income (AGS, 2004 est., 2005)
Households, Families, and Income, 2004 est.
Fayette Indiana U.S.
Households (2004) 10,462 2,465,349 112,708,665
Families (2004) 7,191 1,659,694 75,740,018
Households with children (2004) 3,482 864,296 40,102,709
Average Household Income 51,906 57,000 63,396
Per capita income 22,059 22,807 24,583
Rank for Ave HH Income High-Low 57 28th of 51
Rank for Per Cap Income H-L 31 25th of 51
Average Age of Householder 45-54 yrs. 45-54 yrs.
Source: GIS in Prevention, Fayette County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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5.9 Families (by type)
Table 5.9a: Types of Households with Children (AGS, 2004 est., 2005); Median Family Income (AGS, 2004 est., 2005)
Types of Households w/ Children and Median Family Income, 2004 est. (AGS, 2005)
County Hamilton Co. Indiana U.S.
HHs w/ children (2004) 36,645 864,296 40,102,709Married Couple Family (Percent) 84.1 70 69Lone Parent Male (Percent) 3.9 6.9 6.8Lone Parent Female (Percent) 11.4 21.8 23.2Non-family Male Head (Percent) 0.5 1.1 0.8Non-family Female Head (Percent) 0.1 0.2 0.2Median Family Income 86,222 54,393 54,087Rank for Married Couple Family (% of HHs w/ children) 1 26th of 51 Rank for Median Family Income 1 21st of 51
Source: GIS in Prevention, Hamilton County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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6.12a Crime Indices
Table 6.12b: Specific Crimes, Indices (AGS Crime Risk 2004, 2005)
Crime Indices, 2004 (AGS, 2005, based on FBI UCR)
County DeKalb Indiana U.S. IN Rank in US
Total Crime Index 17 93 101 30th of 51
Personal Crime Index
14 74 101 26th of 51
Property Crimes 17 110 102 27th of 51
Crime Indices, 2004 (AGS, 2005, based on FBI UCR) -- Rankings
DeKalb IN Rank in US
Rank Total Crime Index 75 30th of 51
Rank Personal Crime 75 26th of 51
Rank Property Crimes 71 27th of 51
Source: GIS in Prevention, DeKalb County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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6.12b Crime Indices
Table 6.12b: Specific Crimes, Indices (AGS Crime Risk 2004, 2005)
Crime Indices, 2004 (AGS, 2005, based on FBI UCR) Tippecanoe Indiana US
Personal Crime Index 48 74 101
Murder Index 48 107 100
Rape Index 104 94 101
Robbery Index 27 76 101
Assault Index 45 70 101
Property Crime Index 97 110 102
Burglary Index 86 98 102
Larceny Index 153 109 102 Motor Vehicle Theft Index 41 142 101
Crime Indices, 2004 (AGS, 2005, based on FBI UCR) -- Rankings
Tippecanoe IN Rank in US
Rank Personal Crime 16 26th of 51
Rank Murder 31 18th of 51
Rank Rape 7 28th of 51
Rank Robbery 15 25th of 51
Rank Assault 30 29th of 51
Rank Property Crime 12 27th of 51
Rank Burglary 15 21st of 51
Rank Larceny 4 24th of 51
Rank Motor Vehicle Theft 14 7th of 51
Source: GIS in Prevention, Tippecanoe County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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6.18 Food Stamp Recipients
Table 6.18: Food Stamp Recipients per Month in 2004 (FSSA, Division of Family and Children, 2005) and Rate per 1,000 Total Population for 2004 and 2005 and Change in Rate (calculations from the IPRC based on data from FSSA, Division of Family and Children, 2004 and 2005).
CSAP calculates this as the average number of persons who receive food stamps each month, stated as the rate per 1,000 persons in the total population. This statistic for Indiana comes from Indiana Family and Social Services Administration, Family Resources Bureau as reported in the Indiana Youth Institute Kids Count in Indiana 2005. The rate calculation comes from the Indiana Prevention Resource Center. The following table shows the rate for 2004 for Marion County with comparisons for the state and nation.
Food Stamps, 2004 (FSSA, Family Resources Bureau, 2006)
Marion Indiana
Population, 2004 864,200
6,230,346
Food Stamp Recipients per mo., 2004 104,832
516,360
Rate per 1000 persons, 2004 121.3 82.9
Rate per 1000 persons, 2003 105.1 73.1
Change in Rate per 1,000 from 2003 to 2004 16.2 9.8
Rank for 2004 Rate per 1,000 Persons 3
Source: GIS in Prevention, Marion County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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Stage Two:Analyzing Data and Custom Mapping
Property Crime Indices
To show County
Relative to IN and US Rates
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Map: Property Crime Indices
Bottom Quarter, Mid Range, Top Quarter (includes over IN & over US)
Above US (9), 101.55-194
Above IN (12), 95.55-194
Top Quarter (23), 64-194
Mid Range (46), 19-64
Lowest Quarter (23), 4-19
AGS, Crime Indices2004 (2005)Indiana Prevention Resource Center
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How GIS Helps You Obtain Funding
Provides Demographic Background
Facilitates Profile of Needs/Resources
Documents Locate Problem Area/ Target Audience
Helps Justify Decisions about Strategy Selection
Explains Aspects of Cultural Competency
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Outcomes-Based Prevention
Substance- related problems
Effective Prevention:
Intervening Variables
Strategies/Programs
Planning, Monitoring, Evaluation and Re-Planning
Source: U.S. Department of Health and Human Services, SAMHSA, CSAP
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Outcomes-Based Prevention
Sustainability & Cultural Competence
Source: U.S. Department of Health and Human Services, SAMHSA, CSAP
Profile population needs, resources, and readiness to address
needs and gapsMonitor, evaluate,
sustain, and improveor replace those that
fail
Develop a Comprehensive Plan
Implement evidence-based prevention
programs andactivities
Mobilize and/or build capacity to address needs
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How GIS Helps Obtain Funding
Source: U.S. Department of Health and Human Services, SAMHSA, CSAP
Assessment CONVINCE THEM
OF THE NEED
Describe Your PlanBase on Literature, Logic Model
Step-by-Step BlueprintBuild in Evaluation
CapacityHighlight AWARENESS,
WHAT YOU BRINGWHAT YOU GAIN
Evaluation: Plan for on-going Monitoring
and Evaluation
Implementation:Explain Rationale for choice
of evidence-based strategyand activities
Cultural CompetenceSustainability
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III. GIS for Program Evaluation (a Stage Two Activity)
Create a Risk/Protection Surveillance System
Track Change
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GeocodingFailed TRIP Inspections
Indiana Prevention Resource Center
Source: IN State Excise Police, TRIP
Source: GIS in Prevention, County Profiles, Series 3 (Indiana Prevention Resource Center, 2006)
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Schools in Proximity to Failed TRIP Inspections
Indiana Prevention Resource Center
Source: IN State Excise Police, TRIP
Allen County
Source: GIS in Prevention, Allen County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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Schools in Proximity to Failed Trip Inspections
Clark County
Source: GIS in Prevention, Clark County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
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Schools in Proximity to Failed Trip Inspections, Close-up
Clark County -- Clarksville
Source: GIS in Prevention, Clark County Profile, Series 3 (Indiana Prevention Resource Center, 2006)
Middle School
Outlet SellingTo Minor
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IV. GIS for Research
Conduct Research to Identify Relationships among Environmental and Health Variables
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What You Have Learned:
• Components of GIS system and costs• How GIS Can Help You with Program Planning
– Obtain Demographic Background– Profile Needs, Resources– Locate Problem Area or Target Audience– Inform Decisions about Strategy Selection– Enhance Cultural Competency– Obtain Funding
• How GIS Can Help You with Program Evaluation– Create a Risk/Protection Surveillance System– Track Change
• How GIS Can Help You Do Research– Conduct Research to identify relationships among
environmental and health variables