gis in prevention, county profiles, series 2 1 the indiana prevention resource center gis in...

1 GIS in Prevention, County Profiles, Series 2

THE INDIANA PREVENTION RESOURCE CENTER

GIS in Prevention County Profiles Series, No. 2

Orange County, Indiana

Barbara Seitz de Martinez, PhD, MLS, CPP

The Indiana Prevention Resource Center at Indiana University is funded, in part, by a contract with the Indiana Family and Social Services Administration, Division of Mental Health and Addiction, financially supported through HHS/Substance Abuse Mental Health Services Administration, Center for Substance Abuse Prevention, Substance Abuse Prevention and Treatment Block Grant. The IPRC is operated by the Department of Applied Health Science and The School of Health, Physical Education and Recreation.

GIS in Prevention, County Profiles, Series 2

GIS in Prevention County Profile Series, No. 2


Barbara Seitz de Martinez, PhD, MLS, CPP

Project Staff:

Indiana Prevention Resource Center

Opinions expressed herein are those of the authors, and not necessarily those of the Trustees of Indiana University or the Division of Mental Health and Addiction. Indiana University accepts full Responsibility for the content of this publication. ©2005 The Trustees of Indiana University. Permission is extended to reproduce this County Profile for non-profit educational purposes. All other rights reserved.

Solomon Briggs, BA, GIS TechnicianRobin Canfield, BAParul Kaushik, MPHJennifer Hoffman

Bilesha Perera, MSc, PhDMegan Randall, BASusan Samuel, MSc, MSNicole Smith


Orange County

The maps and tables in this publication were prepared using PCensus7.06 for MapInfo and MapInfo Professional 7.0.


Acknowledgements

This edition of the PREV-STAT™ County Profiles is dedicated to the memory of Mr. William J. Bailey, MPH, CPP, past Executive Director of the Indiana Prevention Resource Center, whose vision for the application of GIS to prevention led him to launch PREV-STAT™ in the Spring of 2002.

Primary thanks are due to the project staff – Bilesha, Jennifer, Megan, Nicole, Parul, Robin and Solomon – whose hours of work brought this effort to completion. During the course of our year’s work on this project, Bilesha Perera completed his PhD and Parul Kaushik completed her MPH in Applied Health Science. Jennifer Hoffman and Nicole Smith progressed to near completion of their MPH degrees. Megan Randall completed her BA in Journalism; Robin Canfield her BA in Computer Science; and Solomon Briggs, a recent I.U. graduate, completed his A+ Certifications in computer hardware and software.

This second edition of the full County Profiles includes information gathered from multiple agencies and sources, including the Alcohol and Tobacco Commission, the Indiana State Excise Police Tobacco Retailer Inspection Program (TRIP), and the Indiana State Police Forensics Laboratory for methamphetamine data, the Family and Social Services Administration, and the Indiana Business Resource Center. Thanks go out to all the agencies that make their rich data available to the public. Special thanks to Major Steve Anderson, State Director of the Indiana Tobacco Retailer Inspection Program (TRIP) and to Dave Heath, Chairman of the Alcohol and Tobacco Commission. Special thanks to Desiree Goetze, Coordinator of TRIP at the Indiana Prevention Resource Center, for her support and advice. Special thanks also to Sergeant Dave Phelps of the Indiana State Police Forensics Laboratory for sharing data on methamphetamine laboratory seizures.


Acknowledgements, cont.

Thanks, too, to Steve Turner, who has provided online search engine access to a subset of the data from the full County Profiles, offering access to multiple years and multiple variables for each of several data topics. The new search engine, launched in April, will be a major focus for development during the up-coming year.

Serving as Deputy Director of the IPRC while continuing to direct the PREV-STAT™ Service certainly contributed to making this a very memorable year of challenges and opportunities. It has been a year of much personal and professional growth. For this opportunity and for all their assistance and support throughout the year, I thank Dr. Mohammad Torabi, Chair of the Department of Applied Health Science and Interim Executive Director of the IPRC, Joyce F. Arthur, all my co-workers at the IPRC, and Sally Fleck, Office of Mental Health and Addiction, Family and Social Services Administration. Finally, my thanks to my husband, for his love and encouragement.


The Bill Bailey I Remember

Bill knew poverty. In conversations at work he recounted memories from his childhood that troubled him still, and that moved him to select the field of public health. He worried about the children who wore their house key on a string and had no one to care for them after school. Bill cared about the elderly. He worried about the old folks who lacked access to medical care. He recounted memories of elderly women in his home town, who ate dog food and suffered malnutrition because they could not afford both food and medicines.

Bill loved children. His life was about improving their chances for health and happiness. The assets approach to prevention appealed tremendously to him, because it celebrated the beauty of childhood and what is right and wholesome: parents bonding with their children; children bonding with their school and other mentoring adults; and the community of neighbors, the community of faith embracing the children and providing them with healthful activities and strong values, attitudes and beliefs.

Bill believed in Everyman. He believed in the power of the people to solve their own problems. At the same time, he believed in the responsibility of government to provide a safety net for the disadvantaged, young and old.

Bill was about finding solutions. He was a master at identifying simple solutions to complex problems. Bill studied a situation in all its complexity and reduced it to its simplest basic components, positive and negative. He drew attention to those key elements. Then he found ways to attack the negatives at their point of greatest vulnerability, and to celebrate the positives to multiply their impact. He strived for efficiency and economy of means, calling this “Precision Targeting in Prevention.” He targeted youth 10-14 because those are the “critical years.” He targeted the gateway drugs, and he targeted the after school hours from 3-6 p.m. because they are the “critical hours.” He launched a campaign for science-based prevention strategies and programs before “science-based” became a national mandate.


The Bill Bailey I Remember

He envisioned a State where children would have healthy alternative activities in the after school hours. He invested hundreds of hours in grant-seeking and won the largest prevention grant in the history of the state, establishing after school programs in cities across the state. By doing so he demonstrated the value of this innovative approach and positioned Indiana as a leader in the nation.

Bill was a visionary. He foresaw the monumental educational force of the internet and concentrated his energies and resources in the early and mid 1990s into building the first major drug information portal of any state prevention resource center. Only the federal National Clearinghouse of Drug Information was bigger. Bill was work personified. The hours he poured into the building, maintenance and expansion of the IPRC web site consumed his evenings and weekends. His scholarly articles and his students continue to influence the future of prevention and public health.

Bill was a visionary and an innovator. He foresaw the power of desktop publishing to reach the most people with the greatest efficiency and for the least cost. He foresaw the power of mapping to inform prevention planning and decision-making. He called it “creating a statistical picture of your community” and he squeezed the power of that software at a time when it was in its infancy and its potential had not yet evolved. He labored for hundreds of hours to produce maps, which today would take minutes. But by doing so he demonstrated the value of this innovation and justified major investment in it, positioning Indiana again as the leader in the nation in this approach to prevention.

Bill loved to talk and share stories, and had a fantastic sense of humor. Those who worked with him will always remember his vigor and enthusiasm for story-telling. The stories were about real people, real issues, and demonstrated how much he cared and how much he wanted to make a difference. Bill did make a difference at many levels and in many lives: at the personal level for those who knew him, and in the history of prevention for decades to come for those touched by the programs he helped to put in place. He will be sorely missed.


Background

This is the second edition of The PREV-STAT™ GIS in Prevention County Profiles Series, which includes one volume for each of Indiana’s 92 counties. This edition will join last year’s on the IPRC web site.

Microsoft PowerPoint was selected as the medium for presentation, because PowerPoint (PP) facilitates development of the publication and because PP allows users access to data and maps that is not possible with other formats (e.g., Adobe pdf files). Using proper citation, the user can copy maps and tables from the County Profile PP slides for use in public presentations, documents, and spreadsheets for their prevention needs. For help with such manipulations of the County Profile components, please call the IPRC (800/346-3077 in Indiana).

Following the appearance of last year’s first edition of the full profiles, the PREV-STAT™ GIS in Prevention County Profiles Fact Sheet Series was published, presenting highlights from the full profiles in the form of 92 fact sheets, one per county. These are also available on the IPRC web site.

In addition to providing data, this publication serves a training function, both introducing people to the IPRC’s PREV-STAT™ Service and promoting the goals of the Imagine Indiana Together Framework and the Strategic Prevention Framework, promoting infrastructure development and understanding of how data can be applied to prevention. The County Profiles are at once an application and a training tool. They increase both the return for investment of the IPRC PREV-STAT™ staff, databases and hardware, and also the effectiveness and efficiency of prevention efforts across Indiana. In addition to being available via the internet, individual Profiles can also be made available on CD ROM, upon request.

This year a major focus will be enhancement of the search engine component of the PREV-STAT™ Service and web site.


Table of Contents Summary

1. Introduction: Raising Smoke-Free Kids

2. PREV-STAT™ Overview

3. Geographic and Historical Notes

4. Protective Factors

5. Basic Demographics

6. Archival Indicators of Risk

7. Complementary Resources

8. Appendices



2. PREV-STAT™ Overview


4. Protective FactorsSchoolsYouth Serving AgenciesLibrariesPlaces of WorshipMap 1: Married Couple Families with ChildrenMap 2: Afternoons R.O.C.K. in Indiana Programs

5. Basic Demographics5.1 PopulationMap 3: Total Population (Equal Count)Map 4: Total Population (Natural Break)Map 5: Total Population (Custom Ranges) Map 6: Percent of Population (Ages 0-4)

Table of Contents


5. Basic Demographics, continued

5.2 Race/EthnicityMap 7: Percent of Population, 2 or More RacesMap 8: Percent of Population, Hispanic OriginMap 9: Percent of Population, African American

PCensus Table 1: Demographics by Block Group and TotalsMedian Family IncomeMedian Household IncomePercent of Housing Units Owner-OccupiedPercent of Housing Units Renter-OccupiedPercent of Housing Units VacantMedian Age

5.3 Marital StatusMap 10: Percent of Population Currently Divorced5.4 Labor ForceMap 11: Renter-Occupied Housing Units5.5 Industry5.6 Occupations

Table of Contents


5. Basic Demographics, continued5.7 Educational AttainmentMap 12: Educational Attainment Less Than 9th Grade5.8 HouseholdsMap 13: Median Household IncomeMap 14: Average Household Income5.9 Families5.10 Lifestyles

6. Archival Indicators of Risk

Community Risk Factor: Availability of Drugs6.1 Alcohol Sales Outlets per Capita6.2 Tobacco Sales Outlets per CapitaMap 15: Population of Youths Vulnerable to Tobacco Sales to MinorsMap 16: Failed TRIP Inspections6.3 Availability of Drugs to Youth: Failed TRIP Inspections6.4 Proximity of Failed TRIP Inspections to SchoolsMap 17: Schools in Proximity to Tobacco Outlets That Failed TRIP InspectionsMap 18: Close-up of Schools in Proximity to Failed TRIP Inspections6.4 Proximity of Failed TRIP Inspections to Schools6.5 Clandestine Methamphetamine Lab seizures

Table of Contents


Table of Contents, cont.

6. Archival Indicators of Risk, continued

Community Risk Factor: Transitions and Mobility6.15 Net MigrationCommunity Risk Factor: Extreme Economic and Social Deprivation6.16 Unemployment Rates6.17 Free Lunches/Textbooks, K-126.18 Food Stamp Recipients6.19 Aid to Families with Dependent ChildrenPCensus Table 4: More Demographics by Block Group and Totals (Census 2K, SF3)

Percent of Population over 25 with Less Than a High School DiplomaFamilies with Children under 18 in Poverty (Count)Single Mom with Children under 18 in Poverty (Count)Children under 18 in Poverty (Count)Households with No Vehicle Available (Count)

Map 27: Population under 25 with Less Than a HS Diploma (County by Block Group)6.20 Adults without a High School DiplomaMap 28: Low Educational Attainment, Less Than a High School Diploma (IN by County)6.21 Single Parent Family HouseholdsMap 29: Single Moms with Children under 186.22 Poverty: Total Poverty and Poverty by Age Group6.23 Families with Own Children in Poverty



6. Archival Indicators of Risk, continuedMap 30: Single Moms with Children in Poverty (County by Block Group)6.24 Poverty by RacePCensus Table 5: Child Poverty Statistics by Block Group and Totals (Census 2K, SF3)

Total Children 6-11 (Count)Children 6-11 in Poverty (Count)Children 6-11 in Poverty (Percent)Total Children 12-17 (Count)Children 12-17 in Poverty (Count)Children 12-17 in Poverty (Percent)

Map 31: Children 12-17 in Poverty (County by Block Group)6.25 Poverty: Single Parent Families with Children in Poverty6.26 Lack of Health InsuranceMap 32: No Health Insurance

Family Risk Factor Management Problems:6.27 Children in Homes with No Parent Present

Family Risk Factor: Family Conflict6.28 Divorce RateMap 33: DivorceFamily Risk Factor: Family Attitudes and Involvement6.29 Households Where All Parents Work



7. Complementary Resources7.1 IPRC's PREV-STAT™ County/Local Data Page7.2 STATS Indiana7.3 Statistics from the Indiana Youth Institute7.4 The Indiana Department of Education7.5 The Indiana Criminal Justice Institute7.6 FBI Uniform Crime Report7.7 U.S. Census Bureau American Factfinder7.8 Claritas™ "You Are Where You Live“7.9 SAVI7.10 Social Indicator System (SIS) 7.11 Indiana State Department of Health

8. AppendicesA. Census DefinitionsB. Claritas™ Lifestyle PRIZM ClustersC. County Distribution of Tobacco FarmsD. Archival IndicatorsE. DSA Contact InformationF. State Offices


Map 1: Married Couple Families with ChildrenMap 2: Afternoons R.O.C.K. in Indiana ProgramsMap 3: Total Population (Equal Count)Map 4: Total Population (Natural Break)Map 5: Total Population (Custom Ranges) Map 6: Percent of Population (Ages 0-4)Map 7: Percent of Population, 2 or More RacesMap 8: Percent of Population, Hispanic OriginMap 9: Percent of Population, African AmericanMap 10: Percent of Population Currently DivorcedMap 11: Renter-Occupied Housing UnitsMap 12: Educational Attainment Less Than 9th GradeMap 13: Median Household IncomeMap 14: Average Household IncomeMap 15: Population of Youths Vulnerable to Tobacco Sales to MinorsMap 16: Failed TRIP InspectionsMap 17: Schools in Proximity to Tobacco Outlets That Failed TRIP Inspections (County)Map 18: Close-up of Schools in Proximity to Failed TRIP Inspections

Maps(Indiana by county unless otherwise indicated)


Map 19: Adult Cigarette Smoking, County by Block Groups (Percent)Map 20: Adult Cigar Smoking, County by Block Groups (Percent)Map 21: Adult Cigarette Smokers, Indiana by County (Percent)Map 22: Highest Gambling Rates (Percent)Map 23: Lowest Gambling Rates (Percent)Map 24: Gambling RatesMap 25: Adult Lottery Gambling (Percent)Map 26: Total Crime IndexMap 27: Population under 25 with Less Than a HS Diploma , County by Block GroupMap 28: Low Educational Attainment Less Than a High School Diploma (IN by County)Map 29: Single Moms with Children under 18Map 30: Single Moms with Children under 18 in PovertyMap 31: Children 12-17 in Poverty, County by Block GroupMap 32: No Health InsuranceMap 33: Divorce

Maps



When a child is born, parents, grandparents and other relatives and friends, in whose home the child will spend time, prepare or “childproof” to create a safe and wholesome environment. When the child reaches school age, most parents entrust their child to the school, confident that teachers and school personnel will provide a safe and wholesome environment where the child will continue to thrive. Proactive parents become involved in the school to help guarantee this happens. From birth and throughout life, the child, then adolescent, then young adult experiences more and varied contexts and gains skills needed to appraise and respond appropriately to people, circumstances and events. Through role modeling and many other methods, parents and others help the child and adolescent to master these skills. At the same time, parents and others attempt to protect the child and adolescent from negative influences and from stressors (people, circumstances and events) inappropriate to their age and maturity. This process continues into young adulthood and to an extent throughout life. But inevitably, parents and other caregivers gradually release control over their offspring’s interactions; and gradually the child assumes responsibility for her or his own life.

The child passes increasingly into the hands of society, that is, the communities (school, town, neighborhood, workplace, social group, etc.) in which he or she lives. It is therefore important to be concerned with the larger environment beyond the home for its many influences upon child development. Communities can be defined variously, including geographically and socially. How we define community will depend on the question being asked or objective being sought. Sometimes the geographic and social communities overlap, even coincide; but many times they do not. Geographically the communities in which people live include the global, national and state levels down to the smaller county, block group, neighborhood and household level. Socially people belong to groups that cross all geographic boundaries and that can be described from broad political, socioeconomic, religious, linguistic, ethnic and lifestyle categories, down to the individual school, program, club, religious congregation, neighborhood and nuclear family.


In fact, society has its hands on the child from the beginning, since an individual’s eyes, ears, and mind are constantly being filled with images and sounds produced or supplied by our unique environments. In nearly every corner of the earth and for nearly every child, this includes the electronic media that enters through our televisions, computers, and music players.

Although the notion of child-proofing the world is more than overwhelming, there is much that a parent, neighborhood and community can do to positively influence child development and thus adult behaviors. Ideally, the world should be a safe place for everyone, where everyone could thrive. Those concerned about children need to be concerned with their total environment. Though it is very difficult for a single person or a few individuals to effect large scale change, individual actions and organized efforts by community coalitions and advocacy groups can influence policies, laws and community norms, thus reaching the broader environment and society.

In addition to the ways parents can influence their children’s risk for smoking in the home (e.g., an authoritative child-raising style, communicating disapproval of smoking, and parental non-smoking), a significant factor in adolescent smoking is friends’ smoking behavior. Mewse, et al (2004:64-65) found that the “association between parental smoking and adolescent smoking is mediated by friends’ smoking behavior.” Adolescents’ friends are a powerful influence, as are their parents. The question then becomes: “How can parents influence the smoking behavior of their children’s friends?”

1. Introduction: Raising Smoke-Free Kids, cont.



An answer is “By influencing community norms.” Actually, there are numerous ways to influence the smoking behavior of the child’s or adolescent’s friends. One way is to try to influence the child’s choice of friends. But this is not enough, because as the child ages, the parent’s ability to control or influence becomes more limited.

Another method for influencing youth tobacco behaviors is reducing the availability of tobacco to youth. Since millions of youth in the U.S. purchase cigarettes personally (NHSDA 2002:2), enforcement of laws prohibiting the sale of tobacco to youth is imperative. But this is not enough, because, rather than make a direct purchase, over 60% of youth will ask a friend or relative to buy cigarettes for them. (NHSDA 2002:1-2) In order to discourage this enabling behavior, strategies such as penalties, education and cessation should be put in place to target those who might purchase for youth, i.e., parents, siblings and others of legal age. (CSAP 2000:4)

The task of confronting the availability of drugs in the community involves identifying the locations where drugs are sold and/or produced, as well as reducing the demand. Research finds that although users of drugs are relatively evenly distributed across most communities, the sources of drugs are not. (Saxe 2001:1987-1994)

Advocacy for the establishment and enforcement of policies and laws is another method. Goals of this effort would include: increasing state and local taxes on cigarettes; restricting indoor smoking; regulating and enforcing youth access laws; and state laws regulating purchase, possession and use.



Supporting the appropriate use of the tobacco settlement moneys and state excise taxes for tobacco control efforts is another important strategy. Research shows that if the states and District of Columbia had followed even the minimum recommendation of the Centers for Disease Control and Prevention (CDC) for the amount of money to be spent on tobacco control, the prevalence of youth smoking would have fallen from between 3.3 to 13.5% more than it has. (Tauras 2005:341).

Other strategies involve education, including normative education. According to the CDC, education strategies, when carried out together with community and media activities, have the potential to “postpone or prevent smoking onset in 20 to 40 percent of adolescents.” (CDC 2000:2) The character, timing and duration of school-based programs are all significant. Normative education is important, because it creates awareness of true community norms, countering misperceptions that “everyone is doing it.” Nationally, 75% of 12th graders, 84% of 10th graders, and 91% of 8th graders are not current (past 30-days) smokers. (Monitoring the Future 2004:53).

In order to reduce tobacco use, it is important to understand all the factors that contribute to smoking. For example, poverty and stress have been associated with negative health outcomes, including tobacco use. Bennet, et al (2005), found a positive connection between perceived experiences of racial/ethnic harassment and smoking. Likelihood of smoking was two times higher for African American college students during the 30 days following a perceived incident of racial/ethnic harassment, suggesting tobacco use to cope with psychosocial stress. (Bennet 2005:239)



Appropriate targeting of tobacco prevention efforts requires addressing health disparities. For example, adolescents residing in rural areas are 19% more likely to smoke than their suburban peers. (Eberhardt and Pamuk 2004:1684) The Chartbook confirms “that the reduction and elimination of health disparities among rural populations will require a population approach that is sensitive to local variations in physical and cultural realities.” (Hartley 2004:1677) In addition, it is necessary to consider the subgroups in the community, as well as multiple variables. A study by Subramanian, et al, found that a negative health outcome association with poverty was tied not only to neighborhood of residence, but also to race/ethnicity. In the neighborhoods studied, the health of Blacks was more severely affected by poverty than was the health of Whites, suggesting that “the consequences of neighborhood deprivation may be particularly exacerbated for Blacks, compared with Whites.” (Subramanian 2005:262-263)

Clearly, the answer to the challenge of reducing youth tobacco use requires a multi-faceted approach, involving multiple strategies – policies, practices and programs – components of a comprehensive plan. This approach offers far-reaching impact and benefits over time and space. Prevention happens in communities, and every community is distinct. In order to successfully reduce youth smoking, it is essential to understand the local environment. (NIH 1998:iii) To be most effective, prevention programs and strategies need to be appropriate to the characteristics of the community where they are implemented.

The selection of strategies and programs for a particular community should be based on a thorough assessment, including data describing risk and protective levels, which highlight the problems and resources of the community. Based on this data, the greatest risks and weakest protective factors can be targeted, using the community’s resources and building on the strongest protective factors that characterize that community. (Hawkins, et al, 2004:213) In addition, within the local community, it is also necessary to distinguish between subgroups, because generalized data may be misleading with regard to the reality of subgroups within the community. The PREV-STAT Service is one way to seek a revealing picture of the various groups making up a community.



Community mobilization and awareness policies should target social sources as well as tobacco retailers. Education about underage use and health consequences of smoking can influence social norms, namely, the perceived acceptability of youth smoking and of supplying them with cigarettes. Seeing parents and other adults attempting to quit smoking may also influence youth to not start smoking, as well as reduce the availability of cigarettes from those who have quit smoking. (CSAP 2000:5)

The potential negative impact of friends’ smoking, the fact that many retailers sell to youth and the fact that youth obtain cigarettes through multiple means, should motivate parents and other concerned citizens to become involved in efforts to influence smoking norms in their community. Influencing norms involves more than monitoring your child’s activities and trying to influence her or his choice of friends. It also involves reducing the sources of drugs by enforcing laws prohibiting sales of tobacco products to minors. It involves taking the parental authority and parental disapproval of smoking to a community level. It includes community-wide actions to communicate repeatedly the message that “Our community disapproves of youth smoking and our community will not tolerate the sale of tobacco products to youth.”

One of the most effective ways to address tobacco availability and its use by minors is through comprehensive tobacco control programs, which include adequate training for employees, an adequate number and distribution of inspections in the community, an adequate structure of penalties and fines, plus public awareness about the program (Goetze 2004:2) Indiana is lucky to have such a program, namely, the Tobacco Retail Inspection Program (TRIP) of the Alcohol and Tobacco Commission (ATC) in conjunction with the Indiana Prevention Resource Center (IPRC). This program, described in more detail elsewhere in this publication, has contributed to reductions in availability of tobacco to youth and to an overall reduction in youth smoking in Indiana. (The same principle holds true for influencing underage alcohol use through compliance checks of alcohol retail outlets.)



Research shows that if an individual does not begin smoking before the age of 18, she or he is unlikely to become a regular user of tobacco. Using data from TRIP, the IPRC’s PREV-STAT™ Service has calculated the number of tobacco outlets per 1,000 youth ages 10-17 for each county and for the state (7.2 per thousand). This ratio provides some insight into the density of tobacco’s presence among the population of youth most vulnerable to initiating use and becoming regular users of tobacco. One way to illustrate how this number is useful for communicating relative risk and also the need for citizen support is to describe the rate of outlets per thousand youth in concrete images and familiar terms.

Imagine a hypothetical community where the rate of outlets is 8 per thousand youth ages 10-17. There are 2,000 students in the town’s high school. Eight outlets per 1,000 youth equates to 16 outlets per 2,000 youth. If the 16 tobacco outlets were located within the walls of the school or on its campus, parents and school personnel would be acutely aware of the outlets’ proximity to the students. And if it were discovered that even one of those outlets was selling cigarettes to minors, the reaction surely would be swift and clear. Undoubtedly, violators would be penalized and vigilance maintained. Since we know that high school students move freely about a city, why would parents, educators and others not be equally concerned about outlets located throughout the entire community? Residents should support frequent and emphatic communications to all tobacco retailers, reminding them that the sale of tobacco to youth is not tolerated in their community. And they should support the use of penalties for non-compliance to give weight to this mandate.

The IPRC PREV-STAT™ service has also used TRIP data to create a calculation for the intensity of inspection (ratio of number of inspections to number of retail tobacco outlets). This number gives limited insight into the amount of energy being expended in each county. This number, combined with data on the non-compliance rate and trends over time, gives a fuller picture of progress with regard to community norms and efforts currently being undertaken to change them.



Ideally, all sectors of the community would participate in prevention efforts, including law enforcement, medical, education, business, religious, government, neighborhood and other professionals, practitioners and volunteers. The hope is that the benefits of a comprehensive, multi-strategy combination of evidence-based programs, policies and practices will generally influence community norms towards a non-smoking lifestyle. The hope is that the benefits will ripple across the community, reducing all forms of drug abuse and improving quality of health and quality of life for all its residents now and for future generations.

Department of Health and Human Services (2000). U.S. Public Health Service. Reducing Tobacco Use: A Report of the Surgeon General -- Executive Summary. Atlanta: US DHHS, CDC, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.

Eberhardt, M.S. and E. R. Pamul (2004). “The importance of place of residence: Examining health in rural and nonrural areas,” American Journal of Public Health 94/10, 1682-1686. Goetze, Desiree (2004). “Effectiveness of compliance programs,” Prevention Newsline 4/4, 1-7.

Hartley, David (2004). “Rural health disparities, population health, and rural culture,” American Journal of Public Health 94/10, 1675-1678.

Bibliography



Hawkins, J. David, M. Lee Van Horn, and Michael W. Arthur. (2004) “Community variation in risk and protective factors and substance use outcomes.” Prevention Science 5/4, 213-220

Johnston, Lloyd D., Patrick M. O’Malley, Jerald G. Bachman, and John E. Schulenberg (2005). Monitoring the future: National results on adolescent drug use. Bethesda: NIH.

SAMHSA (2002). “How youths get cigarettes,” The NHSDA Report (November 22).

SAMHSA. CSAP (2000). Social Sources of Cigarettes for Youth: The Problem and Potential Solutions. Rockville, CSAP.

Mewse, Avril, J.J., Richard Eiser, Alan M. Slater, and Stephen E.G. Lea (2004), “The smoking behaviors of adolescents and their friends: Do parents matter?” Parenting Science 4/1, 51-72.

Saxe, Leonard, et al (2001), “The visibility of illicit drugs: Implications for community-based drug control strategies,” American Journal of Public Health 91/12, 1987-1994.

Subramanian, Jarvis, T. Chen, David H Rehkopf, Pamela D. Waterman, and Nancy Krieger (2005). “Racial disparities in context: A multilevel analysis of neighborhood variations in poverty and excess mortality among black populations in Massachusetts,” American Journal of Public Health 95/2, 260-265.


2. PREV-STAT™: Overview

Increasingly, the value of data to decision-making is shaping how people work. Collection and analyses of relevant data facilitates improved quality in all phases of prevention. Better needs assessment enables better planning, better capacity building, better processes, programs, outcomes, evaluations, and grant-writing.

Advances in technology have made the use of data extremely cost effective. In 2002 the Indiana Prevention Resource Center launched a new, free service called PREV-STAT™ for people working in prevention in Indiana. This system uses geographic information system software to analyze demographics and alcohol, tobacco and other drug risk and protective factors down to the neighborhood level. Using GIS software and data from a variety of sources, IPRC staff create county profiles and customized project reports, including maps and tables. Users of this service include such prevention professionals and practitioners as state level officials, agency heads, teachers, community coalition members and program leaders.

PREV-STAT™ enables the user to understand the characteristics of a place, to locate a group of people with particular attributes, or to study a subset of the population of a given locale. Analysis can be done at any level from the state to the county, block group, zip code, neighborhood, or based on any arbitrary selected boundaries. Alternately, a radius can be drawn around a site (e.g., a school, place of worship or prevention program) to be studied. The greatest power of PREV-STAT™ is its ability to zoom in on the very small geographic area!

GIS empowers the prevention landscape by attaching threads to statistics and tying them to precise locations on earth. These locations can be potentially very small, like your neighborhood or the mile radius around your school or prevention program site. GIS gives faces to the statistics by allowing you to


2. PREV-STAT™: Overview, Cont.

study specific groups of people. You can ask either“Who lives here?” or “Where do they live?” Ask “Who lives here?” to learn about people in a specific area (e.g., your county, neighborhood or school district). Ask “Where do they live?” to find out about a target audience you seek to serve, (e.g., single female-headed families with incomes below $30,000). GIS in prevention helps make statistics more meaningful and persuasive.

Purchased databases (e.g., from the U.S. Census Bureau, Applied Geographic Solutions-AGS, Claritas, Health Data Science) provide rich data at the community and neighborhood levels. In addition, asset information is continuously being collected to reflect local resources in the form of prevention programs and other community and youth serving agencies, organization and institutions (e.g., libraries, YMCAs, and religious institutions). Other environmental risk and protective factors represented in PREV-STAT™ include schools, alcohol outlets and locations of tobacco retailers that were found to have sold to minors, and gambling casinos.)

These County Profiles offer statistics at the county level with comparisons to the State of Indiana and U.S. In addition, for many variables there are tables listing statistics by block groups (neighborhoods) for the entire county demonstrate the wide diversity that exists within each county and identifies where in the county there are assets or strengths (e.g., literacy and vehicles for transportation) and challenges or risks (e.g., child poverty). In addition, 32 maps accompany and illustrate demographics, risk and protective factors.

The contents of this volume are intended to advance prevention by providing statistical information for use in the various phases of the prevention process, including community readiness, needs assessment, grant-seeking, program planning, and eventually program evaluation. This series is full of information about the citizens of Indiana, living in her 92 counties: their ages; occupations; incomes; households and families;


2. PREV-STAT™: Overview, Cont.

education; behaviors with regard to alcohol, tobacco, other drugs, and gambling; their assets and their hardships; their resources and their needs. Even so, the information contained in these volumes is incomplete without the insider knowledge that the residents of the counties bring to it. It is hoped that users of this volume will seek to complement this county-level information by requesting custom reports for their neighborhoods and communities from the IPRC PREV-STAT™ Service.

Data will never replace people, who remain the key to success. We talk about data-driven prevention, but people actually remain very much in the driver’s seat. People as individuals and agencies need to collaborate and develop protocols for data collection and data sharing. People at the grassroots need to add their common sense, insider-knowledge to the process to check for missing variables, wrong assumptions, cultural oversights or insensitivities. People select what data will be collected and how. They collect it, analyze it, check its accuracy, use their findings to develop reasonable strategies, practices and programs. They use data in decision-making related to planning, marketing, testing, and implementing. At each step of the way, people use data, including data generated by the prevention activities themselves, to evaluate performance, both in terms of processes and outcomes. Process evaluation uses data to measure such things as the fidelity of program delivery and efficiency in maximizing human and financial capital. Outcome evaluation uses such data tools as pre- and post- tests, surveys and data trends to assess the effectiveness of prevention efforts.

The PREV-STAT™ Service is here to meet your needs. You do not need to have a precise question in mind. We will help you discover how PREV-STAT™ can help you. Just call and ask to speak to someone about PREV-STAT™.


Instructions for How to Access PREV-STAT™:

Access PREV-STAT™ through the IPRC home page: http://www.drugs.indiana.edu/

Click on Resources, then on PREV-STAT™. You will then be on the following pagehttp://www.drugs.indiana.edu/resources/prev-stat/index.html/

From this page you can access:The new search engine of PREV-STAT™ County Statistics (with select statistics from 2002-2005) GIS in Prevention, County Profiles Series, Nos. 1-2. 92 volumes published in 2004 and 2005 GIS in Prevention, County Profiles Fact Sheet Series, No. 1 -- short version (No. 2 up-coming)GIS in Prevention, Tobacco Series, No. 1 (92 volumes, up-coming)Resources for County- and Local-Level Data for Prevention Planning

You can obtain copies of Indiana’s 92 County Profiles in these ways:1. View and print entire files or selected pages from the IPRC web site 2. Download files from the IPRC web site 3. Call or e-mail your request that a file be sent to you on CD ROM

You can obtain a custom report:1. Call or e-mail the IPRC to discuss your request2. Be very patient. Custom reports are done as time permits3. You can only request one report at a time4. Demand may limit custom reports by any individual per year

Points of access to the PREV-STAT™ Service: 1. www.drugs.indiana.edu 2. 1-812-855-1237, or, in Indiana toll free at 1-800-346-3077

PREV-STAT™, the IPRC GIS-in-prevention service, is available at no cost to prevention professionals and practitioners affiliated with non-profit or governmental organizations or agencies, including schools and religious institutions. The IPRC is continuously working to obtain more data and to use it to produce maps, tables, slides, publications and soon searchable databases to meet your prevention needs.

2. PREV-STAT™: Overview, cont.


Orange County is located in Southern Indiana and is bordered by the following counties: Lawrence to the north, Washington to the east and northeast, Crawford to the south and southeast, Dubois to the west and southwest, and Martin to the west and northwest. U.S. Highway 150 and State Highways 37 and 145 cross the county. Elevation is 600-850 feet. The county’s landscape varies with very steep slopes in the south and northwest, moderate and steep slopes northeast, and some nearly flat areas along the Lost River in the northwestern Orange County. The landscape features hickory and oak trees. The county pertains to the Highland Rim and Pennyroyal and the Kentucky and Indiana Sandstone and Shale Hills and Valleys resource area.

Orange County is on Eastern Standard Time all year. Average daily temperatures are 18٥/39٥ in January and 63٥/87٥ in July. Annual precipitation is about 46 and snowfall about 12-20 inches.

Typically the first freeze of the season occurs October 10-15 through most of the county, and a few days later (October 15-20) in the far southern part of the county. The last freeze usually occurs April 20-25 in southern Orange County and a few days later (April 25-30) in the northern half of the county. The growing season lasts about 163-183 days.

Agricultural activity is mainly in livestock and corn for grain. Less than half of the land is in farms and less than half of that is in cash crops. Almost three-fourths of the cash income is from livestock. Main crops include hay, soybeans, corn for grain and winter wheat. Apples are an important fruit crop, and tobacco is considered a special crop. Livestock include cattle/calves and hogs/pigs. Main natural resources include crushed stone and forestland. Water resources include lake/reservoirs (Orleans and Spring Valley Lakes); the Patoka and Lost Rivers; and several creeks (French Lick, Sulphur, Upper Sulphur, Wolf, Young, and Strampers Creeks).

Communities include the towns of Paoli, which is the county seat, Orleans, and West Baden Springs.


Sources: Map from PCensus for MapInfo; Notes from Indiana Facts: Flying the Colors by John Clements, 1995.


Orange County Tobacco Production & Revenue:

Source: the Strategic Development Group’s “Alternative Agricultural Strategy” (Bloomington, March 15, 2001) report, which is part of Governor Joseph E. Kernan’s “Recipient Final Reports for Office of the Commissioner of Agriculture Grant Programs” (http://www.in.gov/oca/grants/valueadd/VAFinalReports.html):

According to the most recent data available, Orange County ranks 13th in the State for the tobacco income per farm in 1997 as a percent of the average household income for that year. The percent of all farms that produce tobacco is 1.7%. A total of 26 acres in Orange County were devoted to tobacco production on 9 farms. For those 9 farms, tobacco income per farm ($10,775) expressed as a percentage of the Average Household Income for the county ($29,491) was 36.5% in 1997.

Latest figures (from 1997 USDA Census):Rank for acres in tobacco production: 21st Acres in tobacco production: 26Number of farms producing tobacco: 9As a Percent of all farms: 1.7%Rank in IN for percent of all farms: 19th Tobacco income per farm producing: $10,775 Percent of County’s Ave. Household Income: 36.5%

[See appendices for more information.]

3. Location and Historical Notes


Don’t Know Your Block Group Number?

You can find it easily at the American Factfinder Web Site

3. Orange County Block Group Maps


Orange County

Block Groups


4. Protective Factors in Orange County: An Overview

The importance of protective factors in the environment cannot be over emphasized. They can make all the difference between positive or negative outcomes in child development. Decisions and behaviors with regard to substance use and other high risk behaviors are found to be associated with a constellation of risk and protective factors. These factors have come to be regarded as a “descriptive and predictive framework” within which prevention theory and prevention programs are elaborated. (CSAP 2004:3)

The web of influence which affects each individual and group includes individual, family, school, peer and community factors. Among the personal “individual” characteristics that impact decisions and behaviors are personality traits like a tendency toward sensation-seeking, mental health status, and religiosity. Influences within the family include parent-child bonding, parenting practices, parental substance use, and family size. Influences related to a child’s school experience include the quality of the bond formed between the child and school, academic performance, safety versus conflict in the school climate, and enforcement of clear policies. Pressure from peers and positive peer modeling are among peer influences predictive of abstinence from or involvement with drugs. The availability of drugs in the community, norms of use (e.g., adult use and attitudes, and community policies and enforcement), advertising and socioeconomic circumstances all contribute to the influence of community on its individual members. (CSAP 2004:4-9) These are only a few selected examples of how these factors influence youth behaviors with regard to drug use and other risky behaviors.


4. Protective Factors in Orange County:

Many agencies, organizations and institutions in a child’s environment offer highly positive support and can fortify the child, reducing likelihood of high risk behaviors and substance use. Research has found that the resilience of children from very high risk circumstances is related to the protective factors which also comprise part of their environment and which have had positive impacts upon them. These children thrive in spite of negative influences and vulnerabilities. Examples of protective factors include the schools, libraries, churches, and other youth serving agencies and organizations in the child’s community.

Orange County celebrates the presence in its communities of many institutions, organizations and agencies that promote healthy child development. The teachers, program leaders, librarians, religious leaders, and those who fund them deserve the sincere thanks of all the members of the community for their role in developing future generations of healthy, intelligent, caring and civic-minded citizens. The IPRC is collecting information on assets in each county. The following graph reports the number of public and private schools; libraries (including branches); places of worship; and youth serving agencies, organizations or programs which have been identified by the IPRC:

Table 4.1. School data from the Department of Education, library datathe Indiana State Library, churches and youth serving agencies from American Church List and FSSA (2004).

CSAP. Science-Based Prevention Programs and Principles 2003. Rockville: U.S. DHHS, SAMHSA, 2004.

Protective Factors Present in the County (2003 data)

County Orange

Schools 9

Youth Serving Agencies/Programs 9

Libraries 3

Places of Worship 61


Married Couple Families with Children

AGS, Core Demographics,2003 estimates (2004)



Afternoons R.O.C.K.

246 total programs.9 not geocoded due to address problem.27 geocoded tozip code level.

SFY 2004-2005



5. Orange County Basic Demographics

5.1 Population (2003, estimates)

In 2004, Orange County ranked 74 in the state by total population. Table 1a below shows total population, persons per square mile, total number of households, total land and water areas. Table 1b presents population under 24 by age. Both tables present comparisons of Orange county to the state and nation.

Table 5.1b Population by Age Source: (AGS, 2003 est., 2004)

Table 5.1a: Totals: Population, Households, and Geographic Characteristics (AGS, 2003 est., 2004).

Total Population and Geographic Data, 2003 est.

Orange Co. Indiana U.S.

Total Population 19,492 6,193,993 291,456,161

Persons per sq. mi. 48.7 173 82

Total Households 7,817 2,405,369 109,810,264

Land Area (sq. miles) 400 35,867 3,537,438

Water Area (sq. miles) 9 551 256,645

Total Population and Population under 24 by Age

Age Orange Co. Indiana U.S.

0-4 6.7 6.8 6.9%

5-9 7.1 7.2 6.8%

10-13 6 5.7 5.7%

14-17 5.8 5.7 5.7%

18-20 3.5 4.6 4.2%

21-24 4.4 5.3 5.5%


Total Population (Equal Count)

Appendix D, cont.




Total Population (Natural Break)

Appendix D, cont.




Total Population (Custom Ranges)




Percent of Population Age 0-4





5.2 Race/Ethnicity (2003, estimates)

In 2004 Orange County was predominantly white. The following table shows Orange County’s racial/ethnic make-up in percentages compared to the rest of the state and nation:

Table 5.2: Race/Ethnicity, 2003 estimates (AGS, 2003 est., 2004)

Race & Hispanic/Latino Origin, 2003 est. (Percent):

Race/Ethnic Group Orange Co. Indiana U.S.

White 97.9 87.5 75.1

African-American 0.6 8.4 12.3

Asian 0.2 1 3.7

Two or more races 0.7 1.2 2.4

Hispanic/Latino 0.6 4.1 13.8


Percent of Population, 2 or More Races




Percent of Population, Hispanic Origin




Percent of Population, African American




PCensus Table 1: County Demographics

• Median Family Income• Median Household Income• Percent of Housing Units Owner-Occupied• Percent of Housing Units Renter-Occupied• Percent of Housing Units Vacant• Median Age

These statistics come from AGS 2003 (2004).


Table 1



5.3 Marital Status (2003, estimates)

The following table shows the marital status of the population in Orange County compared with the state and nation:

Table 5.3: Marital Status, 2003 estimates (AGS, 2003 est., 2004)

Marital Status, 2003


Never Married 17.6 24.8 27

Currently Married 59.4 53.4 51

Separated 3 4.1 6

Widowed 12 11.1 10

Divorced 8 6.5 7


Percent of Population, Currently Divorced





5.4 Labor Force: (2003, estimates)

The following table shows the percent of persons were not in the labor force.

Table 5.4: Labor Force, 2003 estimates (AGS, 2003 est., 2004)

Population Not in Labor Force (Percent), 2003 est.

Orange Co. Indiana United States

Population by Labor Force (2003) 15,217 4,808,494 226,527,774

Percent of Males Not in Labor Force 32% 26% 29%

Percent of Females Not in Labor Force 43% 40% 42%

Population Not in Labor Force (Percent) 38% 33% 36%


Renter Occupied Housing Units





5.5 Industry (2002, estimates)

The largest industry in Orange County is Manufacturing with 2,520 persons employed; followed by Retail Trade with 961 persons employed; and Health Services with 945 persons employed. Table 4 shows percentages for the top five industries relative to the state and nation:

Blue collar jobs account for 67% of all workers, white collar for 33% of workers.

Table 5.5: Top 5 Industries, 2002 estimates (AGS, 2002 est., 2003)

Top Five Industries, 2002

Industry Orange Co. Indiana U.S.

Manufacturing 29% 23% 14%

Retail Trade 11% 12% 12%

Health Services 11% 11% 12%

Construction 9% 6% 6%

Education Services 6% 9% 9%

White collar workers in all industries 33% 48% 53%

Blue collar workers in all industries 67% 52% 47%



5.6 Occupations (2002, estimates)

The following table lists the occupations in which the highest percent of Orange County residents worked in 2002 with comparisons to the state and nation:

Table 5.6: Top Five Occupations, 2002 estimates (AGS, 2002 est., 2003)

Top Five Occupations, 2002


Machine operators, assemblers & inspectors, 16%

Administrative support occupations, including clerical, 15%


Service occupations, except protective & household, 15%

Precision production, craft & repair occupations, 13%

Professional specialty occupations, 14%

Precision production, craft & repair occupations, 15%


Executive, Administrative, and Managerial, 12%


Professional specialty occupations, 12%


Sales occupations, 9% Sales occupations, 11% Sales occupations, 12%



5.7 Educational Attainment (2003 estimates)

The following table shows educational attainment in Orange County compared with the state and the nation.

Table 5.7: Educational Attainment (AGS, 2003 est., 2004)

Educational Attainment, 2003 (Percent)

Highest Level Orange Co. Indiana U.S.

Less than 9th Grade 10 5 8

9th-12th, No Diploma 16 13 12

High School 45 37 29

Some College, No Diploma 15 20 21

Associate Degree 3 6 6

Bachelor's Degree 5 12 16

Grad or Prof Degree 5 7 9


Educational Attainment





5.8 Households (2003, estimates)

Table 8 shows number of households, families, and households with children, and also included data in comparison to the state and nation.

Table 5.8: Median Age and Household Income (AGS, 2003 est., 2004)

Households, Families, and Income, 2003 est.


Households (2003) 7,817 2,405,369 109,810,264

Families (2003) 5,369 1,626,451 74,008,827

Households with children (2003) 2,663 847,845 39,230,063

Average Household Income 43,957 55,672 60,600

Per capita income 17,953 21,967 23,201


Median Household Income, 2003




Average Household Income





5.9 Families (2003, estimates)

The following tables shows the percent distribution by type of household with children and median family income with comparisons to the state and nation.

Types of Households w/ Children, 2003 est. (AGS, 2004); Median Family Income (Claritas, 2004)


Households with children (2003) 5,312 1,682,671 39,230,063

Married Couple Family (Percent) 74.8 69.9 68.9

Lone Parent Male (Percent) 7.2 6.9 6.8

Lone Parent Female (Percent of HH w Child) 16.7 21.7 23.2

Non-family Male Head (Percent) 1 1.2 0.8

Non-family Female Head (Percent) 0.3 0.3 0.3

Median Family Income (Claritas, 2003 est.) 39,665 51,568 57,801

Table 5.9a: Types of Households with Children (AGS, 2003 est., 2004); Median Family Income (AGS, 2003 est., 2004)



5.10 Lifestyles (Claritas™: Indiana 2003, 2004)

Based upon census data and demographic projections, the Claritas™ PRIZM segmentation system analyzes every neighborhood in the United States according to the opportunities and the influences which impact its residents. Claritas™ has defined 62 different types of neighborhoods, which they call “clusters.” The cluster concept is based on the assumption that “Birds of a feature flock together.” The clusters are defined based on “similarities in income, education, and household type, as well as attitudes and product preferences.” (Mitchell 1995) These clusters are, in turn, assigned to 15 broader categories called Social Groups. An objective of this analysis is to determine demographic variables and lifestyle characteristics to explain customer profile differences. While the driving impetus behind this data is commercial for-profit business, its application value is not limited to that sector. We offer this information in the County Profile Series for its application in the service of prevention.

Table 5.10a: Dominant Lifestyles of Orange County (Claritas™: Indiana, 2003)

See Appendix for explanation of Lifestyles Codes

Claritas' PRIZM Lifestyle, Dominant Lifestyles, 2003

PRIZM NE Orange Co. IN U.S.

T4 - Rustic Living 44.84% 11.22% 11.59%

T3 - Middle America 31.40% 14.17% 10.31%

T2 - Country Comfort 17.38% 15.74% 10.00%

T1 - Landed Gentry 6.38% 12.00% 8.15%

U1 - Urban Uptown 0.00% 1.12% 8.73%



5.10 Lifestyles (Claritas™: Indiana, 2004)

The following table shows the main lifestyles for Indiana households compared with the county and U.S.

Table 5.10b: Dominant Lifestyles of Indiana (Claritas™: Indiana, 2004)

The following table show the main lifestyles for households in the U.S. compared to the county and state.

Table 5.10c: Dominant Lifestyles in U.S., (Claritas™: Indiana, 2004)

See Appendix for explanation of Lifestyles Codes


PRIZM Lifestyles Social Group IN Percent Orange Co. US Percent


T1 - Landed Gentry 12.0% 6.38% 8.2%

S4 - Inner Suburbs 8.5% 0.00% 4.6%

S3 - Middleburbs 8.2% 0.00% 6.2%

C3 - Micro-City Blues 7.5% 0.00% 6.5%


PRIZM Social Group US Percent Orange Co. IN Percent


U1 - Urban Uptown 8.7% 0.00% 1.1%

T1 - Landed Gentry 8.2% 6.38% 12.0%

S2 - The Affluentials 7.6% 0.00% 7.0%

C2 - City Centers 7.3% 0.00% 6.7%


6. Orange County Archival Indicators of Risk

Section 6 explores variables found to be associated with elevated risk for alcohol, tobacco, and other drug problems. This analysis of risk factors is based on the Center for Substance Abuse Prevention (CSAP)’s list of archival indicators as described in “Building a Successful Prevention Program” published on the Western Center for the Application of Prevention Technology (CAPT) web site. CSAP outlines four major categories of risk indicators: community, family, school and individual/peer. A full listing of archival indicators can be found in the Appendix. The Indiana Prevention Resource Center (IPRC) is aggressively pursuing the collection of data for all the archival indicators and offers here additional indicators beyond those suggested by CSAP.

Children form their opinions of human nature and the world based on their experiences and observations. For children the family is the most important institutional influence upon their socialization. (Allison and Lerner 1993) The norms of the child’s domain are critical. Children growing up in a home where parents abuse drugs (Biederman, et al. 2001), in a school where non-drug use policies are not clearly communicated and firmly enforced (CSAP 2004:7), in a community where drug use is tolerated or encouraged (Hogan, et al 2004:43) are at higher risk of becoming involved in substance use. Parenting practices are key to reducing and preventing problem behaviors in youth. (Bigan and Cody 2004:131) An important part of the family and parenting picture is parent role modeling. Parents involved in community service, parents who vote, parents who participate in their child’s life -- do make a difference. Not only do they model what it means to be a parent and an adult, they also communicate norms of behavior through example. This modeling, together with parental monitoring of children’s behaviors and the establishment of high expectations, creates a powerful influence. (Perkins 2004:9) By confronting misperceptions about norms, the social norms approach to prevention strengthens cultures by correcting misunderstandings about the beliefs and values of its members. Several of CSAP’s six prevention strategies aim to change norms and/or to correct misperceptions about them.



This section discusses those CSAP archival indicators for which Indiana data is available and adds several additional related indicators. This report presents data for the following archival indicators:

Category: CommunityAvailability of DrugsCommunity Laws/NormsTransitions and MobilityExtreme Economic & Social Deprivation

Category: FamilyFamily Management ProblemsFamily ConflictFavorable Parental Attitudes and Involvement



Allison, Kevin W., and Richard M. Lerner1993 “Integrating Research, Policy, and Programs for Adolescents and Their Families.”

In Early Adolescence: Perspectives on Research, Policy and Intervention. Richard M. Lerner, ed. Hillsdale, NJ: Lawrence Erlbaum Associates.

Biederman, J., Faraone, S.F., Monuteaux M. C., and Feighner, J.A.2001 “Patterns of Alcohol and Drug Use in Adolescents Can be Predicted by Parental

Substance Use Disorders,” Pediatrics 106, 792-797.

Bigan, Anthony, and Christine Cody2004 “Preventing Multiple Problem Behaviors in Adolescence.” In Reducing

Adolescent Risk: Towards and Integrated Approach. Daniel Romer, ed. Thousand Oaks, CA: Sage. Pp. 125-131

Center for Substance Abuse Prevention2004 Science-Based Prevention Programs and Principles 2003. Rockville, MD.

Hogan, Julie A., Kristen Reed Gabrielsen, Nora Luna, and Denise Grothaus.2003 Substance Abuse Prevention: The Intersection of Science and Practice.

Boston: Allyn and Bacon.

Perkins, H. Wesley2003 “The Emergence and Evolution of the Social Norms Approach to Substance Abuse

Prevention.” In The Social Norms Approach to Prevention School and College Age Substance Abuse. H. Wesley Perkins, ed. San Francisco: Jossey-Bass.

Western CAPT2003 Building a Successful Prevention Program Reno: Univ. of Nevada.


6. Orange County Archival Indicators of Risk Community Risk Factor: Availability of Drugs

6.1 Alcohol Sales Outlets Per Capita

CSAP defines this indicator as the number of alcohol sales outlets in relation to the total population. The following table shows the number of outlets, the total population, the number of outlets per capita, and the approximate number of outlets per every 1,000 residents of Orange county, with comparisons to the state.

Alcohol Sales Outlets Per Capita, (IN ATC, 2005)

Orange Co. Indiana

Total Population (2004 est.) 19,714 6,230,346

Number of Outlets (March 2005) 47 11,011

Outlets Per Capita 0.0024 0.0018

Outlets Per 1,000 Persons 2.38 1.77

Table 6.1: Alcohol Sales Outlets Per Capita, 2004 (Population from AGS 2004, 2005; Number of Outlets from ATC, 2005)



6.2 Tobacco Sales Outlets Per Capita

The Center for Substance Abuse Prevention (CSAP) defines this indicator as the number of tobacco sales outlets in relation to the total population. The following table shows the number of outlets in the county compared to the State. It also reveals the density of outlets per capita for the county by stating the number of outlets for every 1,000 residents and for every 1,000 youth in the county.

Community Risk Factor: Availability of Drugs

Table 6.2: Tobacco Sales Outlets, 2003 (ATC, 2004)

Tobacco Retail Sales Outlets Per Capita, 2003

Orange Indiana

Number of Outlets 18 5,095

Total Population 19,492 6,193,993

Outlets Per 1000 Persons 0.9 0.8

Total Population, 10-17 2,240 710,759

Outlets per 1000 Youth 8.0 7.2


Population of Youths Vulnerable to Tobacco Sales to Minors


Source: AGS Consumer Behavior,

2003 (2004)

Youth Ages 10-17 (2003)


Failed TRIP Inspections

Schools in Proximity to Tobacco Outlets that Failed TRIP Inspections in 2003


Source: IN State Excise Police, TRIP



6.3 Availability of Drugs to Youth: Failed TRIP Inspections

Thanks to the outstanding work of the Tobacco Retailer Inspection Program (TRIP), we have additional data concerning the availability of tobacco products to youth, such as the locations of outlets that sold to youth and the number of total inspections and of failed inspections in each county where inspections were held in 2003. Since the TRIP was established in 2000, the non-compliance rate has decreased each year. For more information on this program, please consult the IPRC’s November 2004’s newsletter, “Prevention Newsline.”

Center for Substance Abuse Prevention Science-Based Prevention Programs and Principles 2003. Rockville, MD.

Howard, K. A., K.N. Ribisl, B. Howard-Pitney, G.J. Norman, L.A. Rohrback

“What Factors Are Associated with Local Enforcement of Laws Banning Illegal Tobacco Sales to Minors?” Preventive Medicine 33, 63-70.

Goetze, D.D. 2004. “Effectiveness of Compliance Programs.” Prevention Newsline 17, 1, 1-6.

The sale of tobacco to youth is a clear indicator of the availability of drugs to youth and of the attitude of at least some members of the community with regard to the seriousness of the issue. Therefore we have included some aspects of the TRIP data here and some aspects under “Community Norms.” The use of compliance checks has been found to be an effective environmental strategy. (Howard, et al. 2001) CASP names “ready access to tobacco” a factor that increases the likelihood of drug use by youth and “active enforcement of youth access laws using unannounced compliance checks” a prevention strategy shown to successfully reduce such sales. (CSAP 2004:8-9) Therefore, CSAP promotes increased levels of enforcement as part of a larger effort to reduce youth smoking. (CSAP 2004:8-9)



6.4 Proximity of Failed TRIP Inspections to Schools

Where drugs are available in areas heavily trafficked by children, the environmental risk is increased (CSAP 2003:8). In addition to the above statistics for TRIP, PREV-STAT™ has geocoded the locations of schools and of failed tobacco inspections to facilitate yet another level of analysis by showing, via maps, the proximity to schools of tobacco outlets that failed TRIP inspections. For the counties that did participate in the TRIP Program, this County Profiles series presents maps for the county with some close-ups. These maps are intended to give a very general picture of the situation in the county and to encourage people to pursue obtaining similar information at the neighborhood level. (The power of PREV-STAT™ is greatest for neighborhood analysis!)

Community Risk Factor: Availability of Drugs

It should be noted that whereas the scale of a map showing the entire county makes it difficult to see much detail, studies of neighborhoods offer great potential for representing the environmental risks and assets. The greatest power of PREV-STAT™ lies in its ability to give extensive data and insights for the very small geographic area. To have a customized study of your neighborhood, call the IPRC and ask for the PREV-STAT™ service.

Center for Substance Abuse Prevention2003 Science-Based Prevention Programs and Principles 2002. Rockville, MD.



Schools in Proximity to Tobacco Outlets that Failed TRIP Inspections in 2003





Close-up of Schools in Proximity to Tobacco Outlets that Failed TRIP Inspections in 2003



Paoli, Indiana



According to the Indiana State Police there were 374 methamphetamine lab seizures in the state of Indiana in the year 2000, 690 in 2001, 999 in 200, 1260 in 2003, and 1549 in 2004. (David Phelps, Indiana State Police, 2005).

Table 6.5: Clandestine Methamphetamine Lab Seizures, 1998-2004 (ISP, 2005)

6.5 Clandestine Methamphetamine Labs Seizures

The discovery of clandestine methamphetamine labs attests to the presence of crystal methamphetamine in the area. Law enforcement officers in Indiana have found that the primary motivation of those individuals mounting methamphetamine labs in this state has been to support their personal addiction rather than to create a market for sales. Nonetheless, the presence of the labs creates the impetus for selling the drug and creates sources for obtaining the drug in the community.

Meth Lab seizures Made by ISP and All seizures (Orange County and Indiana)

Orange Co. (ISP

seizures)Orange Co. (All

seizures)Indiana (ISP

seizures)Indiana (All

seizures)

1998 1 1 43 43

1999 3 3 129 177

2000 6 7 314 374

2001 6 7 542 690

2002 15 15 732 999

2003 12 12 1011 1260

2004 9 9 1113 1549



A child’s view of normal is critically impacted by the child’s environment: the sights, sounds, tastes, textures, and smells of the child’s world: “Infants participate, from birth on, in sociocultural activities that are committed to cultural goals and values . . .” (Keller, et al. 2004) If the child grows up seeing drugs and drug use portrayed in a positive manner on local billboards and local television and modeled at home and elsewhere in the child’s community, the presence of drugs (and hence potential availability) and use of drugs easily becomes the child’s norm. In this circumstance logic suggests it would be “norm-al” for the child to have the expectation that later in life he or she, too, for better or worse, may use drugs. As success tends to beget success, and good parenting practices tend to be replicated by the children raised in that environment, so unfortunately, those who are abused are more likely to become abusers, and those raised in a climate of drug use are more likely to become users.

Community Risk Factor: Community Laws/Norms

The smell of cigarettes, the feel of icy beer bottles and of delicate wine glasses, song lyrics glamorizing drug use, and the over-use of over-the-counter or prescription medications to eliminate every small discomfort creates a notion of normal that impacts the child’s expectations of human behavior, including his or her own. In some instances, it can be difficult to separate family norms and community norms. Many factors contribute to the creation of community norms, including family traditions, public policies, and law enforcement practices. In general, community norms will be the outcome of the beliefs and practices of all the community’s governmental, educational, social, religious, and business enterprises.

Drug use modeling by adults in a community creates an environment that is more hospitable and encouraging of drug use by youth. This modeling takes place within and outside of the home. Since the statistics don’t separate adults from family settings from other adults, we have included adult behaviors with regard to drugs as a community indicator and simply mention it again in the context of family indicators. Still, clearly, this information from a community has strong implications for family settings as well, since one could assume that a significant number of those adults live in family settings. Each County Profile contains several maps and tables comparing the block groups in a county for the counts and percents of adults who smoke cigarettes or cigars, drink alcohol, or gamble. Where possible, indicator data is given in terms of per household amounts.

Heide Keller, et al., 2004 “The Bio-Culture of Parenting: Evidence from Five Cultural Communities,” Parenting: Science and Practice

4/1 (2004):25-50.



6.6 Household Spending on Alcohol, 2003

According to AGS Consumer Spending estimates for 2003 (2004), spending on alcohol products in Orange County per household was $412 and included the following expenditures:


Table 6.6: Per Household Spending on Alcohol (AGS, Consumer Spending, 2003, 2004)

Per Household Spending on Alcohol, 2003 est.


Consumer Spending on Alcoholic Beverages 379 438 461

Spending on Alcohol Outside the Home 162 188 197

Beer and Ale Away from Home 54 62 65

Wine Away from Home 25 29 30

Whiskey Away from Home 41 48 50

Alcohol on Out-of-Town Trips 42 49 52

Spending on Alcohol In the Home 208 239 251

Beer and Ale at home 126 145 152

Wine at Home 52 60 63

Whiskey and Other Liquor at from Home 15 17 18

Other Liquor 15 17 18



6.7 Household Spending on Tobacco, 2003

The following table shows per household spending on tobacco products. To give a better perspective we will compare this figure to household spending on miscellaneous reading materials and on personal insurance.


Table 6.7: Per Household Spending on Tobacco Products, Miscellaneous Reading and Personal Insurance (AGS, Consumer Spending, 2003)

Per Household Spending on Tobacco, 2003, est.


Per Household Spending on Tobacco Products 371 428 444

Cigarettes 337 387 400

Other Tobacco Products 34 41 44

Per Household Spending on Misc. Reading 211 245 257

Newspapers 94 109 114

Magazines 45 52 54

Books 72 84 88

Per Household Spending on Personal Insurance 450 522 553



6.8 Adult Tobacco Behavior

The following table shows adult smoking behavior as percentages for Orange County, with comparisons for Indiana and the nation.


Table 6.8a: Adult Smoking Behaviors (MRI, Consumer Behavior Lifestyle 2003, 2004)

Adult Smoking Behavior, 2003 est. for Population Age 18+


Smoked Cigarettes in last 12 mos. 31.3 29.3 29.3

Smoked Cigars in last 6 mos. 4.8 5.3 5.3


Orange County Tobacco Production & Revenue:

Source: the Strategic Development Group’s “Alternative Agricultural Strategy” (Bloomington, March 15, 2001) report, which is part of Governor Joseph E. Kernan’s “Recipient Final Reports for Office of the Commissioner of Agriculture Grant Programs” (http://www.in.gov/oca/grants/valueadd/VAFinalReports.html):

According to the most recent data available, 26 counties produced tobacco. Orange County was ranked 8th among those counties for the number of acres (407) devoted to tobacco production. Average tobacco income was $13,974 for those farms producing tobacco. These farms represent 12.8% of all farms in the county. Tobacco income, for each farm producing tobacco, represented 37.9% of the figure for average household income in the county that year (1997).

6. Orange County Archival Indicators of Risk Community Risk Factor: Community Laws/Norms

6.8 Tobacco Production

Table 6.8b: Tobacco Production. Kernan’s “Recipient Final Reports for Office of the Commissioner of Agriculture Grant Programs,” Strategic Development Group’s “Alternative Agricultural Strategy” (Bloomington, March 15, 2001)

Tobacco Producing Orange County (Latest figures, from 1997 USDA Census):

County: Orange

Rank for tobacco production (by acreage) 21

Acres in tobacco production 26

Number of farms producing tobacco 9

As a Percent of all farms 1.7

Rank in IN for percent of all farms: 19

Tobacco income per farm producing 10,755

Percent of County’s Ave. Household Income 36.5


PCensus Table 2: Adult Smoking Behaviors, 2003

• Adult Cigarette Smoking (Count)

• Adult Cigarette Smoking (Percent)

• Adult Cigar Smoking (Count)

• Adult Cigar Smoking (Percent)

• Money Spent on Tobacco

• Money Spent on Cigarettes

• Money Spent on Other Tobacco Products

These statistics come from MRI Consumer Behavior Lifestyle (2004).


Orange County, IndianaAdult Cigarette Smoking, 2003 (Percent)


2003 (2004)



Orange County, IndianaAdult Cigar Smoking, 2003 (Percent)


2003 (2004)



Adult Cigarette Smokers, 2003





6.9 Intensity of TRIP Inspections

The IPRC is grateful to Major Steve Anderson, State Director of the Indiana Tobacco Retailer Inspection Program (TRIP) and to Desiree Goetze, Coordinator of TRIP at the Indiana Prevention Resource Center, and to the staff and police officers of TRIP for all the support they have given to this project.

The IPRC has studied the TRIP data generously made available by the Indiana State Excise Police and has created two additional statistical measurements:

1) for the intensity of inspections (the number of inspections relative to the total number of outlets);

2) for the number of inspections per capita for the population of youth most likely to seek access to tobacco, (i.e., youth ages 10-17).

Intensity of inspection can be viewed as one of many possible indicators of the degree of a county’s involvement in activities to create or maintain a community norm that youth access to tobacco is not tolerated.



6.9 Intensity of TRIP Inspections


Table 6.9: Intensity of TRIP Inspections and Related Statistics, Calculations for 2003 Based on Data from the TRIP Program (ATC, Indiana State Excise Police, 2004)

TRIP Inspection Data, Orange Co. (using data from IN State Excise Police), 2003

County Name Orange Indiana

Intensity of Inspection 4.00 1.28

No of Inspections per Capita:

Population Age, 10-17 2,240 710,759

Total No. of Tobacco Retail Outlets 18 5,095

Total Inspections Attempted 72 6,645

Total Inspections Completed 72 6,533

Failed Inspections 4 896

Percent, Failed Inspections 6% 13.7%

Percent, Passed Inspections 94% 86.3%



6.10 Gambling – Casinos

The presence of gambling establishments -- like the presence of tobacco and alcohol outlets, billboards and other forms of advertising – provides information on community environment and would appear to be an indicator of risk for ATOD problems in a community. In 2003 there were no casinos and no horse-racing establishments in Orange County.




6.11 Adult Gambling Behavior

Like the modeling of smoking and drinking, gambling by adults sets a tone for youth expectations about what it means to be an adult. This report includes maps and tables detailing gambling behaviors by persons 18 and older. The following table reports on the number and percent of persons ages 18 and over who gambled in a casino six or more times in the past year and who played the lottery six or more times in the past 30 days. These gambling statistics were projected based on sophisticated demographic analysis by MediaMark Research, Inc. (MRI, Consumer Behavior Lifestyle 2003, 2004).


Table 6.11a: Adult Gambling Behaviors (Casino and Lottery) (MRI, Consumer Behavior Lifestyle 2003, 2004)

Adult Gambling Behavior, 2003 est.


Population 18+ years and older 14,5644,597,0

13216,704,01

7

Gambled in a Casino 6 or more times in 2003 (Count) 218 100,835 4,885,920

Gambled in a Casino 6 or more times in 2003 (%) 1.5 2.19 2.25

Lottery Played 6+ Times in Last 30 days (Count) 2,007 669,148 29,919,525

Lottery Played 6+ Times in Last 30 days (%) 13.78 14.56 13.81



6.11 Adult Gambling Behavior

The following statistics show Hoosier Lottery sales by zip code for the county from fiscal year 2004.


Table 6.11b: Hoosier Lottery Sales by Zip Code, Fiscal Year 2004 (Hoosier Lottery, 2005)

Hoosier Lottery Sales by Zip Code for Orange County for Fiscal Year 2004 (Hoosier Lottery)

Zip Code City Scratch Off Draw Pull-Tabs TOTAL

47432 FRENCH LICK $251,864 $128,614 $380,478

47452 ORLEANS $396,134 $130,783 $23,184 $550,101

47454 PAOLI $697,214 $284,844 $1,512 $983,570

County Totals: $1,345,212 $544,241 $24,696 $1,914,149

IN Totals: $422,608,706 $291,464,296 $18,897,312 $732,970,314


PCensus Table 3: More Adult Gambling Behaviors

• Lottery, Heavy Users (6+ x), last 30 days (Count)

• Lottery Heavy Users (6+ x) last 30 days (Percent)

• Gambled in a Casino 6+ x, last yr., 2003 (Count)

• Gambled in casino 6+ x, last yr., 2003 (Percent)


Highest Gambling Rates

Adult Casino Gambling, 6+ Times in Last Year (Count)

Source: AGS Consumer Behavior, 2002 (2003)Indiana Prevention Resource Center


Lowest Gambling Rates




Gambling Rates





Crime Statistics

People prefer to reside and businesses prefer to locate where they feel safe to move about, to study and to work. Levels of criminal activity in an area constitute an environmental influence on many aspects of life. People plan their lives taking into account levels of danger associated with activities. How late at night is it safe to be out? on foot? by car? alone? with a group?

For a child, the nature of their environment and the behaviors of their family, friends, neighbors, classmates, and community members strongly contribute to the child’s view of the world and of human nature, and to the child’s expectations for his or her own future behaviors and fate. If people close to the child model criminal behaviors or are often victims of the same, the child will likely hold expectations, including fears, of encountering similar future circumstances.

Hence crime statistics are a useful insight into the character of a place and are important to consider in prevention planning. A prevention program needs to be conducted in a safe place and at a time when it is safe for people to attend. The prevention professionals planning the program could consider specific activities designed to confront, enhance, or offer alternatives to norms and role modeling prevalent in the child’s world.

Data about crimes, arrests and convictions is not collected in any one central location in the state of Indiana at this time.




6.12 Crime Indices

One of the best sources of data available for Indiana at this time is the Crime Risk database published by AGS, who use the FBI’s Uniform Crime Report. Because the level and methods of reporting information to the FBI vary by jurisdiction, information about specific crimes should be viewed as a general indicator rather than for exact precision or exact comparisons.

The AGS Crime Risk Index describes the risk of various types of crime in a given geographic area (e.g., city or state) by comparing the rate of crime in that location to the rate of crime in the nation as a whole. The crime rate for the U.S. is set to 100 for all crimes. Hence a rate of 200 means that the risk of crime in that place is twice as high as for the nation as a whole. (Think of these numbers not as counts of criminal incidents, but as degrees of risk. Hence, an index of 200 means that while the risk of this crime is x per 1000 persons for the nation as a whole, it is 2x per 1000 for the community in question). The following table shows the Crime Indices for Total Crime, Property Crime and Personal Crime. This table shows indices for Orange County, compared to Indiana and the nation.


Table 6.12a: Total Crime, Property Crime, and Personal Crime Indices, 2003. (AGS Crime Risk 2003, 2004)

Crime Indices, 2003


Total Crime Index 19 91 100

Personal Crime Index 25 92 100

Property Crime Index 13 90 100



6.12 Crime Indices

The following table shows the Crime Indices for specific property and personal crimes. The method is to compare the risk in a given location to the general crime risk for the nation as a whole. We see that in the context of the U.S., Indiana is generally safer than other places for risk of robbery, but is more dangerous for risk of murder. See the Appendix Glossary for definitions of these crimes. This table shows indices for Orange County, compared to Indiana and the nation (which is the point of comparison).


Table 6.12b: Specific Crimes, Indices (AGS Crime Risk 2003, 2004)

Crime Indices, 2003


Total Crime Index 19 91 100

Personal Crime Index 25 92 100

Murder 49 111 100

Rape 32 94 100

Robbery 7 73 101

Assault 13 90 101

Property Crime Index 13 90 100

Burglary 18 90 100

Larceny 12 93 100

Motor Vehicle Theft 8 86 101


Total Crime Index

AGS, Crime Indices2003 estimates (2004)




6.13 FBI Uniform Crime Reports, 2002 (2004)

The following data comes directly from the FBI Uniform Crime Report as published by the University of Virginia Library website in September 2004. (There is a link from the PREV-STAT™ County/Local Data Page on the Indiana Prevention Resource Center web site.) The first table presents juveniles crimes, including drug arrests. The most recent data available is from 2002.


Table 6.13a: All Arrests, including Drug Arrests, 2001 (FBI Uniform Crime Reports)

FBI UCR All Arrests, 2002: Orange

Coverage 0

Alcohol-Related Arrests

Liquor Law Violation 41

Driving Under the Influence 105

Drunkenness 29

Drug Possession: 35

Marijuana 25

Opium/Cocaine 3

Other Drug Possession 3

Other Dangerous Narcotic 1

Synthetic Drug Possession 4

FBI UCR All Arrests, 2002: Orange

Sale/Manufacturing of Drugs 10

Marijuana Sale/Manufacture 4

Opium/Cocaine Sale/Manufacture 3

Synthetic Drug Sale/Manufacture 2

Gambling 0

Sexual Offenses

Prostitution & Communication 0

Sex Offenses 5

Select Behaviors

Disorderly Conduct 14

Runaway Juveniles 14

Weapons Violations 4



6.13 FBI Uniform Crime Reports, 2002 (2004)

The following data comes directly from the FBI Uniform Crime Report as published by the University of Virginia Library website in September 2004. (There is a link from the PREV-STAT™ County/Local Data Page on the Indiana Prevention Resource Center web site.) This table presents juvenile arrests for crimes, including drug arrests, for 2002.


Table 6.13b: Juvenile Arrests, including Drug Arrests, 2001 (FBI Uniform Crime Reports)

Juvenile Arrests, FBI UCR, 2002 (2004) Orange

Drug Abuse Sale/Manufacture 1

Marijuana Sale/Manufacture 0

Opium/Cocaine Sale/Manufacture 0

Synthetic Drug Sale/Manufacture 0

Drug Abuse Violations - Total 4

Gambling 0

Select Behaviors:

Disorderly Conduct 3

Runaway Juveniles 14

Sex Offenses 0

Weapons Violations 1

Juvenile Arrests, FBI UCR, 2002 (2004) Orange

Coverage 0

Number of Agencies in County Report Arrests 2

Total Co. Population - Agencies Reporting Arrests

19556

Alcohol-Related Arrests:

Liquor Law Violation 8

Driving Under the Influence 1

Drunkenness 1

Drug Possession (Subtotal) 4

Marijuana Possession 3

Opium/Cocaine Possession 0

Other Drug Possession 0

Other Dangerous Non-Narcotics 0

Synthetic Narcotics Possession 0



6.14 Alcohol-Related Crashes

The Indiana Council on Drugged and Dangerous Driving through the Indiana Criminal Justice Institute publishes crash data for each county. The most recent of data on drivers involved in fatal crashes by blood alcohol content of the driver are included in the following tables:

Table 6.14a.: Drivers Involved in Fatal Crashes by Blood Alcohol Content of the Driver, 2001 (Indiana Criminal Justice Institute, 2003)

No. %Total Drivers Involved 13 100%BAC=>0.01--0.07 g/dl 1 8%BAC=0.08+ g/dl 3 23%

Drivers Involved in Fatal Crashes and Blood Alcohol Concentration (BAC) of the Driver, 2001Orange County



6.14 Alcohol-Related Crashes, Cont.

Table 6.14b: Estimated Percent of Alcohol-Related Fatalities and Drivers with BAC 0.08 or Greater in Fatal Crashes, 1994 and 2001 (Indiana Criminal Justice Institute, 2003)

The Indiana Council on Drugged and Dangerous Driving through the

Indiana Criminal Justice Institute publishes crash data for each county. The following table compares figures for 1994 and 2001 for the estimated percent of alcohol-related fatalities and drivers with BAC 0.08 or greater in fatal crashes.

1994 2001BAC=>0.01 0% 44%BAC Above Legal Limit (.10 (1994) and .08 (2001)) 0% 23%

Estimated Percent of Alcohol-Related Fatalities in 1994 and 2001Orange County



For studies of a local neighborhood, the Department of Education web site offers information on retention and drop-out or transfers from neighborhood schools. The IYI web site offers data for the county on graduation rates, drop out rates, etc.

Community Risk Factor: Transitions and Mobility

Table 6.15: Net Migration (STATS Indiana, 2004)

6.15 Net Migration

An excellent indicator of the “transitions and mobility” indicator is the figure for net migration. Data from the STATS Indiana web site reveals that in 2003 net domestic migration for Orange County was 258 and net international migration was 5.

Net Migration, 2002 to 2003 (STATS Indiana, 2005, U.S. Census Bureau):

OrangeRank

in State

Indiana

Net Domestic Migration (change 2002 to 2003) 134 65 1,019

Net International Migration (change 2002 to 2003) 12 59 11,147

Natural Increase (Births Minus Deaths ) 29 21 27,045



Extreme deprivation, either due lack of sufficient funds for basic necessities or due to lack of sufficient social support (e.g., parenting, mentoring and role modeling) has known detrimental implications for child development and creates a high risk environment for the community. This section will explore data related to various forms of extreme deprivation in the county. The archival indicators included by CSAP for this risk factor include unemployment, free and reduced school lunch, Aid to Families with Dependent Children, Food Stamp recipients, adults without a high school diploma, and single parent households. To these variables, PREV-STAT™ adds total poverty statistics, child poverty by age group, and single-parent families living in poverty, and lack of health insurance coverage.

Community Risk Factor: Extreme Economic and Social Deprivation

Table 6.16: Unemployment Rates, January of 2000, 2001, 2003, 2004, 2004 from the Bureau of Labor Statistics, for county and Indiana reported by www.stats.indiana.edu/laus/laus_view3.html.

6.16 Unemployment Rates:

Unemployment rates from the U.S. Bureau of Labor Statistics.

Unemployment Rates - January (Percents)


2000 8.4 3.8 4.1

2001 9.2 4.4 4.2

2002 11.6 5.9 5.6

2003 10.3 5.5 5.7

2004 10.4 5.6 5.6


6. Orange County Archival Indicators of Risk Community Risk Factor: Extreme Economic and Social Deprivation

Table 6.17: Percent of Children Eligible for Free Lunches/Textbooks, K-12, 2003 (*Department of Education, Division of School and Community Nutrition Programs, 2004), 2002 (** Ibid., 2003), and the Change from 2002 to 2003.

6.17 Free Lunch/Textbooks, Grades K-12

The following table shows the percent of students in grades K-12 who received free lunch and textbooks in 2003 and in 2002 according to the Department of Education, and the change from 2002 to 2003, for Orange county and for the state.

Free Lunch/Textbooks (DOE), 2003 (2004)

Orange Co. Indiana

Percent of Students Eligible for Free Lunch/Textbooks in 2003 27.6 24.6

Percent of Students Eligible for Free Lunch/Textbooks in 2002 27.7 25.1

Change from 2002 to 2003 -0.1 -0.5



Table 6.18: Food Stamp Recipients per Month in 2003 (FSSA, Division of Family and Children, 2004) and Rate per 1,000 Total Population for 2003 and 2002 and Change in Rate (calculations from the IPRC based on data from FSSA, Division of Family and Children, 2003 and 2004).

6.18 Food Stamp Recipients

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 2004. The rate calculation comes from the Indiana Prevention Resource Center. The following table shows the rate for 2003 for Orange County with comparisons for the state and nation.

Food Stamp Recipients in 2003 (FSSA, Family Resources Bureau)

Orange Co. Indiana

Total Population, 2003 est. 19,492 6,193,993

Food Stamp Recipients/mo, 2003* 2,074 452,654

Food Stamp Recipients (monthly rate per 1,000 persons), 2003 106.4 73.1

Food Stamp Recipients (monthly rate per 1,000 persons), 2002 92.8 64.2

Change in Rate per Thousand from 2002 to 2003 13.6 8.9


6. Orange County Archival Indicators of Risk Community Risk Factor: Extreme Economic And Social Deprivation

Table 6.19: Temporary Aid to Needy Families as Rate per 1,000 Total Population (*data from FSSA, Division of Family and Children)

6.19 Temporary Aid to Needy Families (TANF) (Aid to Families with Dependent Children, AFDC)

CSAP calculates this indicator as the rate of persons of all ages who participate in the Aid to Families with Dependent Children (TANF in Indiana), stating the rate as the number per 1,000 persons. This table shows the average monthly average statistics for families and for recipients from Orange County and for Indiana as reported by the Indiana Family and Social Services Administration, Division of Family and Children. PREV-STAT™ has calculated the rate of TANF recipients per month per 1000 residents of the county.

TANF Statistics for 2003

County Orange Indiana

Total Population 19,492 6,193,993

Average Monthly Cases 132 52,478

Average Monthly Persons 348 146,649

Rate of TANF per 1000 Persons 17.9 23.7


PCensus Table 4: More Orange County Demographics

• Percent of Population Over 25 with Less Than a High School Diploma

• Families with Children under 18 in Poverty (Count)

• Single Mom with Children under 18 in Poverty (Count)

• Children under 18 in Poverty• Households with No Vehicle Available

These statistics come from U.S. Census 2000, SF3 Indiana.


Orange CountyEducational Attainment: Less Than a H.S. Diploma

Census 2K SF3




6.20 Adults without a High School Diploma (2003, estimates)

Lack of education places a person at extreme disadvantage in many areas of life, including health and income potential. CSAP calculates this risk factor as the percent of persons aged 25 and older who have reached 9th-12th grades but without obtaining a high school diploma. The following table presents 3 statistics for persons over 25 in Orange County: the percent who have not completed 9 th grade; the percent who attended high school but did not graduate; and the percent whose educational attainment is less than a high school diploma (the sum of the first 2 statistics), compared with the state and the nation. This information points to need and also is important to prevention planning for marketing and for activities involving parents and other adults.

Community Risk Factor: Extreme Economic And Social Deprivation

Table 6.20: Adults Who Have Not Finished High School (AGS, 2003 est., 2004)

Percent of Population Ages 25+ with Less Than High School Diploma, 2003 (AGS)


Less than 9th grade 10 5 8

9th to 12th grade, no diploma 16 13 12

Less Than a HS Diploma (Percent) 26.3 17.9 19.6


Low Educational Attainment






6.21 Single Parent Family Households

CSAP calculates this risk factor as the percent of family households with a spouse absent. The following table reports the percent of households with children where one parent is absent.

Table 6.21: Single Parent Families (AGS, 2003 est., 2004)

In addition to the above risk factors listed by CSAP, PREV-STAT™ includes additional basic demographic statistics on total poverty, child poverty and poverty by age group, single parent families living in poverty, lack of health insurance, and households with no vehicle.

Single Parent Households, 2003 (AGS, 2004)



Married Couple Family (Percent) 74.8 69.9 68.9

Lone Parent Male (Percent) 7.2 6.9 6.8

Lone Parent Female (Percent of HH w Child) 16.7 21.7 23.2

Percent of All Households w/ Children Where 1 Spouse is Absent 23.9 28.6 30.0


Single Moms with Children under 18





Risk Factor: Poverty

Poverty can be calculated based on the total population or subsets of the population. It can be expressed as a count of persons or as a percent of persons. The poverty statistics presented in this report come from the 2000 U.S. Census, SF3 figures published in 2003.

Looking at the total population of persons living in a place, the poverty rate can be expressed as the number or count of persons living in poverty or as the percent of the total population in poverty. For example, in Indiana, as of the 2000 census, there were 559,484 persons living in poverty or 9% percent of the total population. This means that 9 of every 100 persons living in Indiana lived in poverty. By age, 2 of every 100 Indiana children ages 6-17 in the year 2000 lived in poverty, hence 2%.

Looking at the population of persons who live in poverty (that 9% of the total population), it can be very useful to understand what their ages are. If we consider all persons living in poverty in Indiana as a group, we learn from the 2000 Census that of that group 11% were between the ages of 0 and 4 years, 2% were 5 years old, 11% were 6-11, and 9% were 12-17 years old.

This description of poverty risk factors will report on total poverty and poverty by age group, on poverty and child poverty as percent of all persons living in poverty, poverty by race, and on single parent families in poverty.



6. Orange County Archival Indicators of RiskCommunity Risk Factor: Extreme Economic And Social Deprivation

Table 6.22: Poverty and Child Poverty as Percent of Total Population (Census 2K, SF3+ Indiana)

6.22 Poverty: Total Poverty and Poverty by Age Group

As of 2000, there were a total of 2,345 persons living in poverty in Orange County. By age group there were 166 persons under 6; 655 persons aged 6-17; 1,182 persons 18-64; and 342 persons 65 and older. The following table shows total poverty and the aforementioned age statistics as percent of the total population of Orange County with comparisons to the state of Indiana and the nation. For example, for Indiana, we see that of all children under 6 years of age in the State, 1% of them live in poverty.

Poverty Statistics - Percent of Total Population, 2000


Total Persons 12% 9% 12%

Under 6 1% 1% 1%

6 to 17 4% 2% 3%

18 to 64 6% 5% 7%

65 and over 2% 1% 2%



Table 6.23: Families with Own Children in Poverty (Claritas 2003 Updates, 2004)

6.23 Families with Own Children in Poverty, 2003

The following table of 2003 estimates presents various statistics concerning families with own children that live in poverty: percent of families with own children that live in poverty, percent of married couple families, percent of single fathers, percent of single mothers, and percent of single parents for Orange county and for the state.

Families in Poverty as Percent, 2003

County Orange Co. Indiana U.S.

Percent of Families w/ Own Children Below Poverty Level As Percent of All Families w/ Own Children 14.1 11.6 15.2

Percent of Married Couples w/ Own Children Below Poverty 6.6 4.1 6.9

Percent of Single Fathers w/ Own Children Below Poverty 23.3 22.2 25.1

Percent of Single Mothers w/ Own Children Below Poverty 45.8 34.9 39.8

Percent of Single Parents w/ Own Children < 18 Below Poverty 39 31.8 36.5



Single Moms Below Poverty

Claritas, Core Demographics,2003 estimates (2004)


No. of Single Mothers w/ Children under 18 Below Poverty as Percent of All Single Mothers with Children under 18.




Table 6.24: Poverty by Race, 2000 (U.S. Census 2K, SF3 Indiana)

6.24 Poverty: Poverty by Race

In the effort to understand the dynamics a community, its needs and how best to design and carry-out prevention programs to meet those needs, it is helpful to analyze data by many different variables. Poverty is an example of how this principle applies. Rates of poverty differ not only between age groups but also in conjunction with other variables, such as race/ethnicity and marital and parenting status. PREV-STAT™ can help the prevention professional look at such combinations of variables to identify an area of need or to better understand a target audience. First we report on poverty and race, secondly on marital status, parent status and poverty (single parents in poverty).

Poverty Statistics by Race (Percent of Group in Poverty), 2000


Black 53% 23% 25%

Asian 14% 16% 13%

Hispanic/Latino 0% 18% 23%

White 12% 8% 9%


PCensus Table 5: Child Poverty

• Total Children 6-11 (Count)

• Children 6-11 in Poverty (Count)

• Children 6-11 in Poverty (Percent)

• Total Children 12-17 (Count)

• Children 12-17 in Poverty (Count)

• Children 12-17 in Poverty (Percent)



Orange CountyChildren 12-17 in Poverty

Census 2K SF3



PCensus Table 5: Child Poverty

• Total Children 6-11 (Count)• Children 6-11 in Poverty (Count)• Children 6-11 in Poverty (Percent)• Total Children 12-17 (Count)• Children 12-17 in Poverty (Count)• Children 12-17 in Poverty (Percent)



PCensus Table 5, cont.




Table 6.25: Single Parent Families as Percent of All Persons in Poverty (Census 2K, SF3 Indiana)

6.25 Poverty: Single Parent Families with Children in Poverty

The following table shows the various types of households with children under 18 living in poverty with comparisons to the state and the nation.

Families in Poverty as Percent, 2003


Percent of Families w/ Own Children Below Poverty Level As Percent of All Families w/ Own Children 14.1 11.6 15.2

Percent of Married Couples w/ Own Children Below Poverty 6.6 4.1 6.9

Percent of Single Fathers w/ Own Children Below Poverty 23.3 22.2 25.1

Percent of Single Mothers w/ Own Children Below Poverty 45.8 34.9 39.8

Percent of Single Parents w/ Own Children < 18 Below Poverty 39 31.8 36.5


Claritas, Core Demographics,2003 estimates (2004)


No. of Single Parents w/ Children under 18 as Percent of All Single Parents with Children under 18

Single Parents Below Poverty




Table 6.26: Insurance Coverage, 2003 (MRI, Consumer Behavior Insurance 2003, 2004)

6.26 Lack of Health Insurance

We consider lack of health insurance to be a form of extreme deprivation. Research has shown that two of the strongest indicators of self-reported health status and routine preventative care are having a consistent source of medical care and having health insurance. Where either is absent there is a higher risk of health problems and particularly of not receiving preventative care. Lack of health insurance is often associated with lack of employment or underemployment, poverty, being in transition, and/or undocumented immigrant status. The following table shows rates of health insurance coverage for Orange County, compared with Indiana and the nation.

Percent of Adult Population with No Medical or No Dental Insurance, 2003 est. (2004)


Current Population Age 18 + 14,564 4,597,013 216,704,017

No Medical Insurance 26.82 26.29 27.71

No Dental Insurance 73.24 66.74 65.97


No Health Insurance

AGS, Consumer Behavior, Insurance2003 estimates (2004)




No one lives in isolation. We all belong to a community, and, actually, to many communities simultaneously. We belong to our immediate family, our extended family, our neighborhood, our town and our nation, to name a few. Others might include religious communities, clubs, school and work. We all want our community, our county, and our state to be a great place to study, to work and to live.

Many risk factors affecting families have been presented in earlier sections of this volume (e.g., poverty, unemployment, single parent status, and lack of health insurance). The analysis presented here is at the level of the county, state and nation, but PREV-STAT™ can easily analyze at the level of the neighborhood, where prevention is most effectively undertaken. Therefore, you are encourage to call the Indiana Prevention Resource Center and take advantage of the PREV-STAT™ Service to support your work in prevention in your neighborhood and community.

CSAP archival indicators of family risk include Family Management Problems, Family Conflict, and Family Attitudes and Involvement, issues which impact most intensely in the confines of the home. Other statistics that are available and would be of relevance in this category are child abuse and neglect.

Family Risk Factor: Management Problems



Family Risk Factor: Management Problems

6.27 Family Risk Factor: Children in Homes with No Parent Present

CSAP defines this risk indicator as the children living in homes with neither parent. It calculates this indicator as a rate (the sum of children living in a household headed by a male or female not the parent plus children living in group quarters divided by the sum of all the types of home circumstances in which children might live, times 100). The following table shows the percent of all households with children where no parent is present for this county, compared to the state and the nation.

Table 6.27: Households with Children with No Parent 2003 (AGS, 2003 estimates, 2004)

Households with No Parent Present, 2003 (AGS, 2004)



Non-family Male Head (Percent) 1 1.2 0.8

Non-family Female Head (Percent) 0.3 0.3 0.3

Percent of All Households w/ Children Where No Parent in Present 1.3 1.5 1.1



6.28 Divorce Rate

CSAP defines family conflict in terms of the divorce rate. Another statistic which CSAP does not mention, but which would be relevant to this risk factor, would be rates of domestic violence in households with children.

Family Risk Factor: Family Conflict

Table 6.28: Divorce Rates (AGS, 2003 est., 2004)

Divorce Rate, 2003 (Percent)


Divorced (Percent)

8 6.5 6.5


Divorce

AGS, Core Demographics2003 estimates (2004)




6.29 Family Risk Factor: Households Where All Parents Work

One way to measure involvement is to look at households where every available parent is working. In Orange County, according to the 2000 Census SF3, the following percents of children were living in households where both parents work. For comparison, all families with children are included in the table.

Family Risk Factor: Family Attitudes and Involvement

Table 6.29: Parents in the Work Force, 2000 (U.S. Census 2000, SF3 Indiana)

Parents in the Labor Force (Children under 18), 2000


Living with 2 parents 77% 74% 72%

Both parents in labor force 49% 48% 43%

Father only in labor force 22% 22% 22%

Mother only in labor force 4% 2% 3%

Living with 1 parent 23% 26% 28%

Living with father 6% 6% 6%

In Labor Force 5% 5% 5%

Living with mother 18% 20% 22%

In Labor Force 16% 16% 16%


The IPRC PREV-STAT™ Local/County Data PageSTATS IndianaStatistics from the Indiana Youth InstituteThe Indiana Department of EducationThe Indiana Criminal Justice InstituteThe FBI Uniform Crime ReportThe U.S. Census Bureau American FactfinderClaritas™ “You Are Where You LiveSAVIIndiana Social Indicator SystemIndiana State Department of Health

The purpose of this chapter is to familiarize prevention professionals with sources of county level data available on the internet. This information complements the PREV-STAT™ service and may fulfill your needs. When, however, you need more localized information, such as for a neighborhood, the radius around a site location, or a town or region, the best advice is to call 1-800-346-3077 and ask for the PREV-STAT™ Service. This chapter describes the context of available data into which the PREV-STAT™ Service fits.

The internet sources of information described in this chapter include:

7. Complementary Resources*

*This chapter is based, in part, on Dr. Barbara Seitz de Martinez and Dr. Mindy Hightower King, “Show Me the Numbers,” conference presentation presented throughout the state, including in Allen County at the 14th Annual Conference on Youth, October 1, 2004.


7.1 IPRC’s PREV-STAT™ County/Local Data Page

The Indiana Prevention Resource Center offers, as part of the PREV-STAT™ Service, a web page that lists major sources of statistics at the county and local level that are of interest for prevention planning. Resources linked from this page include the following:

Indiana Sources for County- and Local-Level Prevention Planning Data

Census Data by County

Other Data by County

Youth Data

Economic Data

Crime Data

Health Data

Youth Access to Tobacco Non-Compliance Rates

National Sources for County- and Local-Level Prevention Planning Data

Census Data by County

Census Tract Map Locators

Other Data by County

Health Data

Economic Data



7.2 Statistics from STATS Indiana

For certain kinds of U.S. Census Bureau statistics for Indiana, an excellent source is the STATS Indiana web site (www.stats.indiana.edu), which is prepared by the Business Resource Center of the Indiana University Kelly School of Business and supported by major funding from the Department of Commerce. This site is especially useful for comparing a county to all the other counties in Indiana and the United States. Several statistics in this County Profile come from this web site.

STATS Indiana gives per capita income for the last 4 censuses, starting with 1970, adjusting for inflation. STATS Indiana also shows at a glance how poverty rates for the total population have changed since 1995 until the present.

In addition to information for the state as a whole, for individual counties, for comparisons of counties, for cities, and for townships, it is possible to select an indicator and a level of geography and obtain information.



7.3 Statistics from the Indiana Youth Institute

The IYI web site (www.iyi.org) uses data from a variety of sources including the U.S. Census Bureau, the Department of Education, TANF, the Indiana State Department of Health, CHINS, and the Child Protection Agency. Based on this data, IYI Kids Count Database presents demographic, economic, education, social, health, juvenile crime, and early childhood indicators for both the state and its 92 counties for the years 1990-2003. The IYI database online allows the user to do comparisons across a series of up to about a dozen years, and to do some mapping.

From this web site we gain valuable insight into the state of children, including early childhood, child protection, health, and economic well-being. Statistics on economic well-being includes monthly average of families receiving TANF, monthly average of persons issued food stamps, and the percent of student in the county who receive free lunch and/or textbooks.

STATS on early childhood include the number of children served by First Steps, the numbers of licensed child care centers, child care homes, child care ministries; and the number of licensed child care spaces per 100 children, ages 0-4. Statistics concerning child care vouchers include the annual number of children receiving CCDF child care vouchers, and the monthly average of children on the waitlist for these vouchers.

Child protection statistics from Child Protection Services (CPS, 2003) report cases of child abuse processed and substantiated by CPS in 2003; cases of child neglect processed and substantiated; cases of child physical abuse cases substantiated; child sexual abuse cases substantiated; and an overall child abuse and neglect rate.

Three County statistics relate to Juveniles and the Law. IYI reports the number of juveniles committed to the Department of Correction, the number of status case filings , and delinquency case filing.



7.3 Statistics from the Indiana Youth Institute

IYI statistics from the Indiana Department of Health for health and well-being include live births, including total births, and percent of low birthweight births. Background on the status of mothers from IYI that has implications for the health and well-being of babies includes the percent of mothers who reported smoking during pregnancy; the percent of mothers who received 1st trimester prenatal care; percent of non-married Moms as percent of all births; the number of Moms who were single, under 20 and without a high school diploma; and the birth rate for teens ages 15-17. Three types of death rate data are also given: the total number of infant deaths; child deaths; and teen deaths from accident, homicide, or suicide. In addition, there is data on the number of children enrolled in Hoosier Healthwise and the number of Noncompliance with Youth Tobacco Access Laws (N/A for 2003).

IYI statistics for each county on education, grades K-12, include much of the same information available on the Department of Education (DOE) web site and some county level data on education not found on the DOE web site. The IYI site includes enrollment data information for public schools, K-12; non-Public Schools; home schools; and alternative schools. Also provided are the numbers of public school dropouts and expulsions and suspensions. Related to graduation are both the number and percent of high school graduates. The Department of Education calculates this percentage graduation rate based on the percent of those who enter twelfth grade and graduate the same year. IYI provides this statistic and also an alternative method for calculating graduation rate, which is the percent of the Freshman class that graduates in 4 years. Other statistics gathered from graduating students include the percent who intend to study at a 4-year college and the percent intending to study at a Vocational/Technical School. One additional significant piece of data is the total per pupil expenditure.



7.4 Statistics from the Department of Education

The DOE web site (http://ideanet.doe.state.in.us/htmls/education.html) reports school and school-corporation level data for grades K-12. Data on the site comes from the years 2001-2004. Indicator data include:

enrollment;

attendance;

graduation and dropout data;

ISTEP reading and math scores for each school by grade;

SAT, ACT, and PSAT test scores;

comparisons to the rest of the state;

free and reduced lunch statistics;

suspensions and expulsions (including alcohol and other drug-related)

future plans of graduates

student-teacher ratio

Links to individual schools provide rich background information on the school communities.

The Indiana School Directory contains address and telephone information for all of Indiana’s schools.



7.5 Statistics from The Indiana Criminal Justice Institute

The sections of the Indiana Criminal Justice Institute web site (http://www.in.gov/cji/indexb.htm) which have the most potential relevance to drug prevention professionals include: Drug and Crime Control, Substance Abuse, Traffic Safety, Youth, and Public Information and Education.

One section of the web site include pdf files for all 92 counties, presenting statistics on all licensed drivers by age, the number of drivers in crashes by age, the percent of drivers involved in crashes by age group, and fatal crashes by month. Included in each of these 92 county reports is a table listing the number of alcohol-related crashes in each of the principle municipalities in the county. These municipalities by county tables are also available in a separate pdf file. These county and municipality files presented data from 2000 (as of April 2004). The statistics in section 6.14 of this County Profile come from this web site.

The section on Traffic Safety includes the Council on Impaired and Dangerous Driving 2003 Report, Crash Data (up to 2000), Seatbelt Studies, Alcohol Impaired Driving Reports, and Teenage Driver Reports.



7.6 Statistics from The FBI Uniform Crime Reports

An excellent site for locating FBI Uniform Crime Report data has been created at the University of Virginia Fisher Library (http://fisher.lib.virginia.edu/crime ). This site includes county as well as state level data from 1990-2001 and presents indicators including all arrests, adult arrests, and juvenile arrests. The number of arrests is given for such crimes as burglary; vandalism; drug use, sale, or possession; driving under the influence; weapons violations; assault; and violent crimes.

Crimes reported in county data are divided into two categories: Part I offenses (murder, rape, robbery, assault, burglary, larceny, auto theft, and arson) and Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).

The statistics in section 6.13 of this County Profile come from this web site.



7.7 Statistics from U.S. Census Bureau American Factfinder Web Site

The U.S. Census Bureau (www.census.gov) provides multiple web sites that offer statistics in a variety of forms. One of the most useful sites for prevention professionals and others is the American Factfinder web site, which is a link from the U.S. Census Bureau web site.

This is one site where information at the local level can be obtained, down to the Block, which is smaller than the Block Group. For example, one can learn the Congressional and Legislative districts numbers. Tables and profiles available for any given Block Group from this site include a profile of the general demographic characteristics; general housing characteristics; tenure, household size, and age of householder. Reference maps are also available.



7.8 Claritas’ “You Are Where You Live” Web Site

The Claritas ™ (www.claritas.com) produces market segmentation (lifestyle) databases that offer insights into the character of communities. The “You Are Where You Live” web site is both a service and a promotional sampling of the kind of information Claritas™ market segmentation databases can provide. This site is, at the same time, entertaining and informative. You simply type in a zip code, select a market segmentation system, and then a search presents the five most prominent segments (lifestyles) in your neighborhood. Each lifestyle is described with examples of typical behaviors and preferences. The PRIZM system classifies lifestyles into 62 types; Microvision has 42 distinct types.

The IPRC owns the Claritas™ 2001 database for Indiana (2003), which contain far more detailed information than that which is available on the “You Are Where You Live” web site. Call the IPRC for more information.

The “You Are Where You Live” web site contains lifestyle profiles (both PRIZM and MOSAIC) for every neighborhood in America, searchable by zip code.



7.9 SAVI

SAVI Interactive: Information for Central Indiana communities (www.savi.org)

provides community profiles, data and mapping. It aims to build capacity to improve decision-making. It is intended to serve as a community information resource. It has Census 2000 data. It presents data for census 2000 census tracts and for 1990 block groups. Other types of data are supplied by many local data providers.

It includes data for Indianapolis MSA counties: Boone, Brown, Hamilton, Hancock, Hendricks, Johnson, Madison, Marion, Morgan, Putnam and Shelby.



7.10 Indiana Alcohol and Other Drugs Social Indicator System

Quoting the website (www.sis.indiana.edu) : “The Indiana Division of Mental Health and Addiction created this site to assist communities in the identification of local substance abuse problems. The indicators are presented for each of Indiana's 92 counties to the extent data were available. Social indicators provide valuable information for deciding upon local action in response to alcohol and other drug problems.

Social indicator data will be updated annually as information from available data sources become available. . “

The “State of Indiana Demographics” section contains data from the 2000 Census. The PREV-STAT™ County Profiles contain more current information for many of these variables.



7.11 Indiana State Health Department

The section named “Data and Statistics” of the Indiana State Health Department web

site ( http://www.in.gov/isdh/ ): contains information on Health Behavior Risk Factors (BRFSS), HIV/STD Quarterly Reports, Immunizations, Infectious Diseases, marriages, maternal and child health, mortality, natality, tuberculosis, and the Youth Risk Behavior Survey (YRBS).



Appendices

A. Census Definitions

B. Claritas™ Lifestyle PRIZM Clusters

C. County Distribution of Tobacco Farms

D. Archival Indicators

F. DSA Contact Information

G. State Offices


A. Census Definitions

The following is an excellent source of definitions and explanations of geography-related terms used by the U.S. Census 2000: http://www.census.gov/geo/www/tiger/glossary.html

Block Group (BG) A statistic subdivision of a census tract. Includes all blocks whose numbers begin with the same digit in a census tract. For example, for Census 2000, BG3 within a census tract includes all blocks numbered from 3000 to 3999. BGs generally contain between 300 and 3000 persons, with an optimal size of 1,500 people.

Census Tract (CT) A small, relatively permanent statistical subdivision of a county or statistically equivalent entity. Designed to be relatively homogeneous units with respect to population characteristics, economic status, and living conditions at the time they are established. CTs generally contain between 1,000 and 8,000 persons, with an optimal size of 4,000 people. CT numbers range from 001 to 9999.

Rural All territory, population, and housing units located outside of urbanized areas and urban clusters.

Urban All territory, population, and housing units located within urbanized areas and urban clusters.

Urban area. A generic term that refers to both urbanized areas and urban clusters. This terminology is new for Census 2000.

Urban cluster (UC) A densely settled area that has a census population of 2,500 to 49,999. A UC generally consists of a geographic core of block groups or blocks that have a population density of at least 1,000 people per square mile, and adjacent block groups and blocks with at least 500 people per square mile.

Urbanized area (UA) A densely settled area that has a census population of at least 50,000. A UA generally consists of a geographic core of block groups or blocks that have a population density of at least 1,000 people per square mile, and adjacent block groups and blocks with at least 500 people per square mile. A UA consists of all or part of one or more incorporated places and/or census designated places, and may include additional territory outside of any place.


A. Census Definitions, cont.

The following is an excellent source of definitions and explanations of social, economic and housing characteristics and general terms used by the U.S. Census 2000: http://www.census.gov/prod/cen2000/phc-2-a.pdf

Labor Force. All people classified in the civilian labor force (i.e., employed and unemployed people), plus members of the U.S. Armed Forces (on active duty).

Group Quarters. Includes all people not living in households. Includes institutionalized population and non-institutionalized population (such as college dormitories, military quarters, and group homes, and the staff residing at these quarters.

Household. A household includes all of the people who occupy a housing unit. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room occupied as separate living quarters. The occupants may be a single family, one person living alone, two or more families living together, or an other group of related or unrelated people who share living quarters.

Spouse (husband/wife) A person married to and living with a householder. People in formal marriages, as well as people in common law marriages, are included.

Child. A son or daughter by birth, a stepchild, or an adopted child of the householder, regardless of the child’s age or marital status. The category excludes sons-in-law, daughters-in-law, and foster children.

Own child. A never-married child under 18 who is son or daughter of the householder by birth, marriage (a stepchild), or adoption.



Family Type. A family includes a householder and one or more other people living in the same household who are related to the householder by birth, marriage, or adoption. Not all households contain families, since a household may be comprised of a group of unrelated people or of one person living alone.

Income of households. This includes the income of the householder and all other individuals 15 years old and over in the household, whether they are related to the householder or not.

Income of families. The incomes of all members 15 years old and over related to the householder are summed and treated as a single amount.

Median income. The median divides the income distribution into two equal parts: one half of the cases falling below the median income and one-half above the median.

Per capita income. The mean income computed for every man, woman, and child in a particular group (dividing the total income of a particular group by the total population in that group).

Industry. The classification system consists of 265 categories for employed people, classified into 14 major industry groups (developed from the 1997 North American Industry Classification System, NAICS).

Occupation. Consists of 509 specific occupational categories for employed people arranged into 23 major occupational groups (developed based on the Standard Occupational Classification, SOC, Manual: 2000).



Poverty Status. The Census Bureau uses the federal government’s official poverty definition. The Social Security Administration developed the original poverty definition in 1964, revised in 1969 and 1980. . . . Since the UDSA’s 1955 Food Consumption Survey showed that families of three or more people across all income levels spent roughly one-third of their income on food, the SSA multiplied the cost of the Economy Food Plan by three to obtain dollar figures for the poverty thresholds. Poverty thresholds vary by family size and composition. Poverty thresholds are revised annually to allow for changes in the cost of living as reflected in the Consumer Price Index. The poverty thresholds are the same for all parts of the country – they are not adjusted for regional, state, or local variations in the cost of living. The weighted average threshold for 3-person families was $13,032 for three adults; $13,410 for 2 adults and a child; and $13,423 for 2 children and 1 adult.

Individuals for whom poverty status is determined. All people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. They are considered neither “poor” nor “nonpoor.”

Household poverty data. Poverty status is not defined for households --- only for families and unrelated individuals.

Race. The concept of race, as used by the Census Bureau, reflects self-identification by people according to the race or races with which they most closely identify. These categories are socio-political constructs and should not be interpreted as being scientific or anthropological in nature. Furthermore, the race categories include both racial and national-origin groups.

Vehicles available. Show the number of passenger cars, vans, and pickup or panel trucks of 1-ton capacity or less kept at home and available for the use of household members.


B. An Explanation of Claritas™ Household PRIZM Groups Related to 5.10 Lifestyles (Claritas™: Indiana, 2004)

Based upon census data and demographic projections, the Claritas™ PRIZM segmentation system analyzes every neighborhood in the United States according to the opportunities and the influences which impact its residents. Claritas™ has defined 62 different types of neighborhoods, which they call “clusters.” The cluster concept is based on the assumption that “Birds of a feature flock together.” The clusters are defined based on “similarities in income, education, and household type, as well as attitudes and product preferences.” (Mitchell 1995) These clusters are, in turn, assigned to 15 broader categories called Social Groups. An objective of this analysis is to determine demographic variables and lifestyle characteristics to explain customer profile differences. While the driving impetus behind this data is commercial for-profit business, its application value is not limited to that sector. We offer this information in the County Profile Series for its application in the service of prevention.

The following 15 PRIZM social groups, which are referenced in this County Profile, are defined largely by degree of urbanization, from the rural countryside to the urban high-rise, and by degree of socioeconomic status determined by such factors as income, education, occupation and home value. Within any one of the 15 social groups, clusters can exhibit very different habits. Studying the details of the PRIZM groups and clusters can inform marketing, advertising, and other planning decisions.

It should be noted that, with reference to degree of urbanization, the term “second city” refers to cities that are not characterized by urban living. These cities are also called “edge cities” because life there is somewhere in between the styles of life in an urban metropolitan city like Chicago or New York and life in a rural country setting. (Mitchell 1995)


An Explanation of Claritas™ Household PRIZM Groups Related to


S1. Elite SuburbsU1. Urban UptownC1. 2nd City SocietyT1. Landed GentryS2. The AffluentialsS3. Inner SuburbsU2. Urban MidscaleC2. 2nd City CentersT2. Exurban BluesR1. Country FamiliesU3. Urban CoresC3. 2nd City BluesT3. Working TownsR2. Heartlanders R3. Rustic Living

Appendix B, cont.

The following PRIZM lifestyle categories:




S1. Elite SuburbsThis PRIZM social group is characterized by high levels of education, income,

investments and expenditures. There are five clusters identified within this group. Many live in suburbs of major metropolitan cities. They tend to be much more liberal than the C1 group described below. Outside of these shared characteristics, the five clusters in this S1 group differ markedly.

U1. Urban UptownThis PRIZM group is also characterized by affluence and is in second place after

the S1 group for this feature. An indication of the density of market concentration in this group is the fact that 94% of all households fall into the 10 top television markets. Over the past 20 years, the clusters in this group have included many executives and professionals from the fields of finance, business, education and entertainment. Recently the clusters in this group have seen the addition of wealthy Eastern European, Asian and Middle Eastern immigrants.

C1. 2nd City SocietyThis PRIZM group is characterized by high levels of education and income and by the fact that they occupy the top economic rung in hundreds of so-called “second” cities and “satellite” cities. Highly educated, they also have large incomes. Most are home-owners. They hold executives and professional positions in local businesses, in finance, health, law, communications and wholesale. They tend to be much more conservative than suburban peers from the S1 group. There are three clusters in this group.

Appendix B, cont.

The following descriptions are based upon information contained in Summary Lifestyle Descriptions: PRIZM Cluster Narratives (Claritas 2000).




T1. Landed GentryThis is the third most common social group in Indiana. The persons in the four

clusters that comprise this PRIZM group are dispersed across the country over a wide geographic area. They constitute the fourth wealthiest PRIZM group. They are characterized by large families with multiple incomes with school-aged children. Heads of household are well-educated executives and professional. This group is dominated by so-called “techies.” For the most part, these households reside far from the country’s major metro areas, in gorgeous areas along the coast and in our uplands.

S2. The AffluentialsThe 3rd most common social group in the U.S., this PRIZM group is made up of

households living in the major metro area suburbs and having upper middle incomes. They comprise the fifth wealthiest group. They have incomes that are above-average and above-average rentals. Their residences include homes, condos and apartments. Their wide ranging careers include business, public service and technical positions. They commute daily. In other ways the five clusters in this group differ widely.

Appendix B, cont.




S3. Inner SuburbsThis PRIZM group is characterized by being middle income in the suburbs of

major metro areas. Their incomes hover right about the U.S. average. In other ways the four clusters in this social group are very different from one another. Two clusters feature college-educated, white-collar workers, while the other two tend to have high school education and be blue-collar employees. Two clusters are young, one old, the other mixed ages. But each of the four clusters has a distinct employment pattern, lifestyle and geographic location.

U2. Urban MidscaleThis PRIZM group is characterized as the backbone of many neighborhoods in

the fringes of major metro areas. They are middle income. Their average income is below the mean of affluence. They are geographically highly concentrated, with three-quarters of these households living in the five top television markets; and only four percent of this group lives outside of the top 25 television markets. All five clusters in this PRIZM social group have high potential for density and ethnic diversity. They employ public transportation. And they cope with urban life, both its perks and its risks.

Appendix B, cont.




C2. 2nd City CentersOf the 15 PRIZM social groups, this is the 4th most common in Indiana. In the

U.S. this PRIZM group lives in the middle-density, midscale satellite cities that surround major metro areas, and also in smaller cities describes as second-tier. Cost of living is lower in their communities, helping them to be better off compared to peers belonging to the U2 group. Most but not all of the five clusters in this group tend to be predominantly white. In other ways these five clusters differ in terms of their ages, marital status, education, careers, and lifestyles.

T2. Exurban BluesThe 5th most common social group in Indiana, this PRIZM group is

characterized by residence in low-density, midscale towns located on the outskirts of major metro areas and so-called second cities. This group has compares to the S3, U2, and C2 groups. Three of its five clusters are predominantly white, have an even distribution in terms of age, are home-owners, married and raising children.

Appendix B, cont.




R1. Country FamiliesMore households in Indiana belong to this group than to any other. This

PRIZM group has recently come to rival the S3, U2, C2 and T2 groups in terms of their midscale affluence and, because their cost of living tends to be lower, they suffer poverty less than these other four groups. Country families are found widely dispersed across the country in small towns and in remote exurban centers, they fall into all but a few of the television markets. They are characterized as married couples with children, white, and working in industrial and agricultural employments. They are home owners and owners of mobile homes.

U3. Urban CoresThis PRIZM group suffers the highest poverty ratios and has the lowest income

of any PRIZM group. The clusters in the U2 group tend to live in big cities in communities described as multi-racial, multi-lingual, with dense population in rental properties (either rowhouses or high-rise apartments). They are characterized by high numbers of single people, single-parents with very young children, and high rates of unemployment.

Appendix B, cont.




C3. 2nd City BluesThis is the second most common social group among Indiana households. This

PRIZM group is characterized by residence in downtown neighborhoods in the nation’s numerous so-called second cities that are found in the fringes of major metro areas. Because the cost of living in their neighborhoods is lower, the persons in the four clusters of the C3 group enjoy more affluence compared to the U3 group, which resides in the bigger cities. While there are some places with unemployment, “broken homes,” and single-parent households, this group also includes a wide spectrum of employment from agriculture to office, retail, clerical, transportation, public service and private sector service.

T3. Working TownsThis PRIZM group is found in exurban and remote towns and in so-called

“satellite” towns that are located outside major metro areas and also outside so-called “second cities.” In general, this group is considered to be better off compared to the U3 and C3 social groups. All four clusters of the T3 group tend to have lower educational attainment and incomes and to work in blue collar jobs. They typically own or rent single-family homes in the midst of beautiful scenery. They enjoy attending religious services. They tend to like doing crafts. In other respects, the four clusters in this group are quite different from one another.

Appendix B, cont.




R2. Heartlanders

This PRIZM group is said to represent the agrarian heartland of the nation. They are found in the Great Plains and in South Central, Mountain and Pacific regions, and in a few isolated locales in the East. Comparatively self-sufficient, the five clusters in this group enjoy a low cost of living. Their families tend to be multi-generational and live in low-density settings in houses and mobile homes. The persons in this group include extremely independent Hispanic/Latinos and Native Americans.

R3. Rustic Living

A higher percent of households in the United States belong to this group than to any other. This PRIZM group is characterized by lower middle income and low cost of living. They are viewed as a promising market for businesses. They live in the very numerous remote towns, hamlets, villages and reservations spread across the country. Married couples and elders share mobile homes, help raise children, and maintain carpools. Employment features craftsmen, agricultural labor, mining, construction and transportation.

Appendix B, cont.




To learn more about these PRIZM groups and the clusters included in each, consult the following web sites:

•http://www.tetrad.com•www.tetrad.com/pub/prices/PRIZM_Clusters.pdf•http://www.claritas.com•http://nhts.ornl.gov/2001/usersguide/appendix_q.pdf•http://www.andreas.com/downloads/geodemographic-clusters.pdf

You can also find a free analysis of your neighborhood by zip code at the Claritas “You Are Where You Live” link from the www.claritas.com web page.

_______________References:

Claritas, Inc.2000 Summary Lifestyle Descriptions: PRIZM Cluster Narratives. Pp. 5-19. Also found at

www.tetrad.com/pub/prices/PRIZM_Clusters.pdf

Mitchell, Susan.1995 “Birds of a Feather,” American Demographics,” February. Also at: http//www.andreas.com/faq-geodemo2.html

Appendix B, cont.


C. Tobacco Production

Source: Tobacco Production. Kernan’s “Recipient Final Reports for Office of the Commissioner of Agriculture Grant Programs,” Strategic Development Group’s “Alternative Agricultural Strategy” (Bloomington, March 15, 2001), p. 11.


D. Archival Indicators

www.westerncapt.org

GIS in Prevention, County Profiles, Series 2 Source: http://www.westerncapt

Archival IndicatorsAppendix D, cont.


Archival Indicators

Source: http://www.westerncapt

Appendix D, cont.


Archival Indicators

See web site for further school and peer indicators: http://www.westerncapt

Appendix D, cont.


E. DSA Contact Information

Source: http://www.drugs.indiana.edu


DSA Contact Information

Source: http://www.drugs.indiana.edu

Appendix E, cont.


F. STATE OFFICESSource: ONDCP web site, STATE OFFICES page: http://www.whitehousedrugpolicy.gov/statelocal/in/stoffices.htmlAllen3

State Education OfficeState Coordinator for Drug-Free SchoolsDepartment of Education Office of Student Services State House, Room 229 Indianapolis, IN 46204–2798(317) 232–0808Fax: (317) 232–6326Web site: http://www.doe.state.in.us

Judicial AgencyDivision of State Court Administration115 West Washington, Suite 1080Indianapolis, IN 46204(317) 232–2542Fax: (317) 233–6586Web site: http://www.in.gov/judiciary/admin

Law Enforcement Planning& State Administrative AgencyIndiana Criminal Justice InstituteOne North Capitol Avenue, Suite 1000Indianapolis, IN 46204(317) 232–1233Fax: (317) 233–5150Web site: http://www.in.gov/cji/home.htm

State Health OfficesDrug and Alcohol AgencyBureau for Chemical AddictionsDivision of Mental Health and AddictionFamily and Social Services AdministrationP.O. Box 7083Indianapolis, IN 46207–7083(317) 233–4454Fax: (317) 233–4693Web site: http://www.in.gov/fssa/serviceaddict/

RADAR Network AgencyIndiana Prevention Resource Center Indiana University, Room 110Creative Arts Building840 State Rd. 46 BypassBloomington, IN 47408–2606(812) 855–1237Fax: (812) 855–49401–800–346–3077 Web site: http://www.drugs.indiana.edu

HIV-Prevention ProgramDepartment of HealthHIV/AIDS Program2 North Meridian StIndianapolis, IN 46204(317) 233–1325Web site: http://www.state.in.us/isdh/programs/hivstd/index.htm


STATE OFFICES

State Offices Policy OfficesGovernor's OfficeOffice of the Governor206 State HouseIndianapolis, IN 46204–2797(317) 232–4567Fax: (317) 232–3443Web site: http://www.in.gov/gov/

State Drug Program CoordinatorGovernor's Commission for a Drug-Free IndianaISTA Building 150 West Market St., Suite 320Indianapolis, IN 46204(317) 232–4219Web site: http://www.drugs.indiana.edu/indiana/gcdfi.html

State Legislative ContactLegislative Services AgencyIndiana House of Representatives/ State Senate200 W. Washington St.Indianapolis, IN 46204–2786House of Representatives (317) 232–9600Indiana State Senate (317) 232–9400Web site: http://www.in.gov/legislative

State Criminal Justice OfficesAttorney General's OfficeOffice of the Attorney GeneralIndiana Government Center South, Fifth Floor302 West Washington StreetIndianapolis, IN 46204(317) 232–6201Fax: (317) 232–7979Web site: http://www.in.gov/attorneygeneral

Corrections AgencyIndiana Department of CorrectionIGCS, Rm E334302 West Washington StreetIndianapolis, IN 46204(317) 232–5715Fax: (317) 232–6798Web site: http://www.in.gov/indcorrection/

Appendix F, cont.

Source: ONDCP web site, STATE OFFICES page: http://www.whitehousedrugpolicy.gov/statelocal/in/stoffices.htmlAllen3


Indiana University Creative Arts 110

2735 E. 10th Street Bloomington, IN 47408-2602

Phone: 812.855.1237 Toll Free in Indiana: 1.800.346.3077

Fax: 812.855.4940E-Mail: [email protected]

WWW: http://www.drugs.indiana.edu/

gis in prevention, county profiles, series 2 1 the indiana prevention resource center gis in...

Documents