Since 1987, the Arrestee Drug Abuse Monitoring Program (ADAM-formerly known as the Drug Use Forecasting Program) has documented the prevalence and type of arrestee drug use across the nation. Unfortunately, this research is limited to urban or metropolitan areas, possibly because of presumed low levels of both crime and drugs in rural areas. The purpose of this paper is to present the importance of researching arrestee drug use in rural areas using data collected from the Rural ADAM Pilot Program. Specifically, this study examines the prevalence and type of arrestee drug use in four rural Nebraska counties and compares these results to those found in Omaha, Nebraska, which is a current ADAM site. Results indicated that arrestee drug use is similar to that in urban areas and the type of arrestee drug use varies across rural counties as well as between rural and urban areas. Most importantly, rural arrestee Methamphetamine use appeared to exceed Omaha arrestee use in one rural area. These findings have substantial implications for planning at the local, state, and federal levels.

INTRODUCTION

A substantial amount of research examines the prevalence of drug use among offenders and contributes to our knowledge on drugs and crime (Belenko & Peugh, 1998; Chaiken & Chaiken, 1990; Brooke, Taylor, Gunn, & Maden, 1993; Peters, Greenbaum, Edens, Carter, & Ortiz, 1998; Warner & Leukefeld, 2001). One of the most instrumental programs in this area is the ADAM program, which tracks the prevalence of drug use among arrestees in 34 sites across the nation (Department of Justice [DOJ], 2000). Specifically, ADAM findings demonstrate that drug use is prevalent among all types of offenders, not just drug offenders; Marijuana is the most prevalent drug among arrestees; multiple drug use among arrestees is often common; and the prevalence of harder drugs such as Heroin, cocaine/crack, and Methamphetamine varies by geographic location.

Unfortunately, ADAM as well as other research in this area traditionally focuses on metropolitan or well-populated areas, neglecting the role of drug use among offenders in rural areas. Urban-based studies rarely reflect the demographic, social, and cultural differences in rural areas and do not address how the findings may or may not apply to rural populations. The absence of rural areas from this research contributes to the impression that rural areas are "safe havens" from such problems; yet, statistics indicate that rural areas face increasing challenges from both drug use and crime. While the characteristics of rural areas (e.g., smaller populations and informal networks) potentially make these areas more vulnerable to the social problems caused or facilitated by drug use and crime, the impression that rural areas are "safe" from the problems of drug use often presents a significant obstacle to securing external funds. In particular, rural areas are less likely to receive funds with little or no data to document the role of drug use among offenders. The purpose of this study is to address this gap in the literature by examining the prevalence of drug use among arrestees in rural areas using ADAM data collected as part of an outreach pilot study. This study will document the prevalence of drug use among rural arrestees, identify which drugs are most significant in rural areas, and compare drug use among rural arrestees to that among urban arrestees in Nebraska.

DRUG USE AND CRIME TRENDS IN RURAL AREAS

In 1981, the U.S. Department of Health and Human Services published a report on rural drug use and found that rural lifetime drug use prevalence rates had increased to two-thirds of nonrural use rates between 1974 and 1979. Based on these trends, the authors predicted that rate differences would disappear entirely if current declining trends persisted (Harrell & Cisin, 1981, p. 1). This prediction came closer to reality at the turn of the 21st century. The 1999 National Household Survey of Drug Use results indicated that past month use for illicit drugs among 18 to 25 year olds was only 4% higher in urban areas compared to rural areas, and among persons 26 and older, the difference was only 1% (Adams et al., 2001). A review of national statistics during this time also showed that drug use was similar across tenth and twelfth graders living in rural and nonrural areas. The most noticeable differences, however, were among eighth graders (Center on Addiction and Substance Abuse at Columbia University [CASA], 2000). Eighth graders living in rural America, for example, were 104% more likely to use amphetamines, including methamphetamine; 50% more likely to use cocaine; 34% more likely to smoke marijuana; 29% more likely to drink alcohol; and 70% more likely to have been drunk than their more urban counterparts (CASA, 2000; see also Donnermeyer, 1992; Edwards, 1997).

Crime trends further illustrate the changing context of rural America. Between 1959 and 1991, rural crime rates increased 420%, and although rate increases were less dramatic throughout the 1990s, increases in the rural rate between 1988 and 1991 (8.6%) far exceeded the urban rate of 3.6%, (Donnermeyer, 1994). Additionally, crime rate decreases during this time benefited metropolitan areas (-20%) and suburban areas (-14%) more than rural areas (-9%) (Donnermeyer, 1994; Uniform Crime Reports, 1996, 1997, 1998, 1999).

While drug use and crime rate trends document the changing context of rural communities and suggest a relationship between the two, they do not provide insight into the role of drug use among arrestees and other criminal justice populations. Surprisingly, there is virtually no data available to document this issue (Leukefeld, Clayton, & Myers, 1992; Moxley, 1992; Wargo, Solomon, Oppenheim, Sharma, & Rom, 1990; Warner & Luekefeld, 2001). Only one report directs specific attention to the role of drug use among criminal justice populations in rural areas. This report (Wargo et al., 1990), Rural Drug Use, provides a summary of trends related to substance abuse arrests, the amount of drugs seized by law enforcement, and scattered prison and jail studies in rural states. A review of these data led the authors to conclude that (1) rural areas had similar arrest rates for substance abuse violations as nonrural areas; and (2) most prison inmates in rural areas had abused Alcohol and/or drugs. The data and findings provided in this review, however, were insufficient to determine the prevalence of drug use among rural arrestees or other criminal justice populations in rural areas.

THE ADAM PROGRAM

Since 1987, the ADAM program has played a key role in documenting the prevalence of drug use among arrestees and the role of drug type in different locations. Over half of all new arrestees, for example, test positive for at least one illicit drug at the time of the arrest regardless of year and location (DOJ, 2000). Additionally, ADAM data provide evidence that the prevalence of drug use varies by both the type of drug and location. For instance, we know from ADAM data that while the prevalence of Marijuana use is similar across sites, the use of harder drugs varies across sites. Whereas Methamphetamine is statistically nonexistent in the Manhattan Borough of New York (0.0% for total male arrestees), Heroin was at 20.5% positive for male arrestees. In Las Vegas, on the other hand, Methamphetamine was far more prevalent (17.8%) than Heroin (4.8%) for all male arrestees (DOJ, 2000). Yet, no such findings are provided for rural areas because ADAM sites are only located in cities with a population of more than 200,000 or a city with the largest population in the state (DOJ, 2000, p. 7). In 1998, the National Institute of Justice recognized the need to expand data collection into less populated areas impacted by drug use and funded the Rural ADAM Outreach Project in Nebraska to pilot this idea.

The need for rural data collection in Nebraska grew from several discussions regarding the growing use of Methamphetamine in both rural and urban areas in Nebraska. Although Omaha ADAM data confirmed an increase in Methamphetamine use from 1994 to 1996 (DOJ, 1997), suspicions of high use patterns in rural areas largely rested on anecdotal evidence rather than quantitative data. Thus, the Rural ADAM Outreach Pilot Project was conducted to determine whether drug use among offenders in rural areas, specifically Methamphetamine, was similar to drug use among offenders in urban areas (for a full discussion of this topic see Herz, 2000). Additionally, these data provided the unique opportunity to understand the nature of drug use among arrestees by addressing the following questions: (1) What is the prevalence of drug use among rural arrestees? (2) What types of drug use are prominent among rural arrestees? (3) How does the prevalence and prominence of drug use compare to those of urban arrestees?

PLACING CONTEXT ON RuRAL NEBRASKA

A significant pitfall in conducting rural research is to categorize all rural areas together since rural communities actually represent a diverse continuum of population, community structure, economic structure, and social support (Conger, 1997; Moxley, 1992). Consequently, three different areas represented by four counties were selected to represent "rural" Nebraska in terms of county size, location in the state, socioeconomic status, and number of arrestees. Additionally, these counties were selected because they processed enough arrestees to produce sufficient sample sizes over a short amount of time.

As shown in Table 1, the population in each of the rural counties is approximately 50,000 or less whereas the population for Douglas County (ie., Omaha) is just under 500,000. The selected areas are unique in several ways, including geographic location, population demographics, and economic features. Geographically, Scotts Bluff County represents the western edge of Nebraska, Hall and Dawson Counties (contiguous counties) represent central Nebraska, and Madison County represents the northeastern section of Nebraska. In terms of population density, Omaha has 1,400 people per square mile, while all rural counties have less than 100 people per square mile. The rural counties also differed from Omaha and each other in terms of racial and ethnic representation. Omaha is more racially diverse than the rural areas with 12% Black compared to 1% or less than 1% in the rural areas. Rural areas, however, are more ethnically diverse than Omaha. The Hispanic population is greater in Hall (14%), Dawson (25%), and Scotts Bluff (17%) Counties than in the Omaha (7%) area. Madison County was an exception to this pattern, where the size of the Hispanic population (9%) was more similar to that in Omaha (Bureau of Census, 2001).

Selected rural areas also differ significantly from Omaha economically. Whereas Omaha has 13,867 nonfarm establishments, rural counties have relatively few (from 712 in Dawson County to 1836 in Hall county), highlighting the agricultural focus of most rural counties in Nebraska. The four rural counties have median household incomes ranging from $30,152 (Scotts Bluff) to $36,880 (Madison County) and all are lower than Omaha, which had a median household income of $42,260. These counties also differ dramatically in terms of those living in poverty. While Madison County has the lowest with 9% of people and 12% of children living in poverty, Scotts Bluff County had 16% of people and 22% of children living in poverty. Omaha figures fell in between rural county figures with 10% of people and 14% of children living in poverty, (U.S. Census Bureau, 2001).

DATA

ADAM data were collected in rural areas and Omaha during October and November of 1998. Arrestees were eligible to participate if they had been arrested and booked within 48 hours of data collection (see DOJ, 2000 for a detailed description of ADAM methodology). Arrestees who agreed to participate were asked to provide a urine specimen and complete an interview, capturing demographic, social and drug use history information. All information collected during this process was anonymous. Data collection in each site was completed using standard ADAM protocol (DOJ, 2000) with only two variations. Due to the low flow of arrestees in rural jails, the typical data collection period (i.e., two weeks) was extended to two months, and data collection times were not standard across sites. In Madison and Dawson Counties, jail staff informed interviewers in the morning and the evening if new arrestees had arrived. Jail staff could also page interviewers when new arrestees arrived using a digital pager. In Hall and Scotts Bluff Counties, jail staff preferred to use a specific time period in the evening to collect information from any new arrestees booked in the previous 24 hours. Staff in these areas also had the ability to page interviewers when arrestees arrived. In Omaha, data were collected for 2 weeks during structured time intervals in morning and evening.

Final sample sizes varied across sites. Table 2 provides a comparison of these sample sizes and the facility population during data collection. As shown in this Table, Scotts Bluff and Omaha samples represented a greater proportion of arrestees processed during data collection than in Madison, Hall, and Dawson Counties. Despite low representation in some sites, demographic comparisons confirmed that the distribution of race, gender, and age did not differ between the sample and the population at any site, providing some confidence in the strength of the sample obtained (see Appendix A). Due to a clerical error, refusal rates were not recorded; thus, it is unclear how many arrestees in the total jail population were asked to participate and refused. The refusal rate for Omaha typically falls between 80% and 90%.

METHODS

To define the prevalence of Alcohol and drug use among rural arrestees and examine whether rural arrestee drug use differed from urban arrestee drug use, analysis of variance and logistic regression were performed. First, arrestee demographics as well as social and charge characteristics were compared across sites in two stages using analysis of variance procedures. These were used to identify whether there were differences across arrestees in rural counties and between arrestees in rural counties (i.e., rural sites aggregated) and Omaha. The characteristics compared included: gender, age, race, ethnicity, most serious charge, education (i.e., completed high school or G.E.D.), and marital status. Table 3 contains the coding scheme for each of these characteristics.

The same analytic procedure was used in the second stage of analysis to compare drug use among rural arrestees in different areas and between rural and Omaha arrestees. To measure drug use, self-report responses to the following questions were utilized:

1. Have you used (alcohol, Marijuana, Cocaine, Crack, methamphetamine) in the past 3 days?

2. Have you used (alcohol, Marijuana, Cocaine, Crack, methamphetamine) in the past 30 days?

3. Have you used (alcohol, Marijuana, Cocaine, Crack, methamphetamine) in the past 12 months?

Additionally, urinalysis results for Marijuana, Cocaine, and Methamphetamine were compared. Self-report responses for Alcohol intoxication at the time of arrest were also included since the ADAM program currently does not test urine for the presence of alcohol.

Logistic regression was used in the final stage of analysis to isolate the effect of location while controlling for arrestee demographic, social, and offense characteristics. Typically, ordinary linear regression can be used to provide an estimate of how powerful the predictor variables are, as well as their rank order in terms of importance. This type of regression also provides an easily interpretable R-squared and standardized coefficients. Mathematically, the R-squared and standardized coefficients of linear regression do not have exact counterparts in more advanced techniques. However, the use of OLS regression requires meeting the assumption that the dependent variable is measured at least on an interval scale, an assumption that is violated with the data in this research, and precludes the use of OLS as an appropriate method of analysis (Liao, 1994). In its own right, logistic regression produces a close correspondence between the observed and predicted conditional means when it is used in predicting the dependent variable, and as such serves as the most appropriate method in determining the relationship between predictor variables and a dichotomous dependent variable (Menard, 1995).

Three regression analyses were performed using the following dependent variables: self-reported intoxication at the time of arrest, urine positive for Marijuana, and urine positive for any drug (except alcohol). Regression models were not estimated for Cocaine and Methamphetamine because low number of cases in at least two of the sites produced unpredictable standard errors and results that were non-interpretable. The independent variables included each rural county with Omaha as the reference category and all of the characteristics listed in Table 3. Although these variables provide a good overview of individual characteristics, there are limitations in identifying them as community indicators. This limitation, however, is unavoidable given that the ADAM interview collects information about the individual and his/her life circumstances rather than characteristics of the environments in which the individual lives.

RESULTS

COMPARISON OF ARRESTEE CHARACTERISTICS

A comparison of demographic and social characteristics yielded four significant differences across rural sites. Three of these differences were found in Hall/Dawson Counties: Hall/Dawson arrestees were less likely female and married but more likely to be Black than arrestees in Madison and Scotts Bluff. Compared to Omaha arrestees, rural arrestees were less likely to be Black and more likely to be Hispanic; less likely charged with violent crimes and more likely charged with drug crimes; less likely to graduate high school or have their G.E.D.; less likely to live with a significant other; and more likely to be divorced.

COMPARISON OF Alcohol AND OTHER DRUG USE

Arrestees' Alcohol and drug use in the past three days, thirty days, and year are displayed in Table 5. A comparison of arrestee responses reveals several drug use patterns across sites. Regardless of location, Alcohol and Marijuana were the most prevalent substances used among this population. Over three-quarters of arrestees reported using Alcohol in the past 12 months (77% to 92%) and one-half or more reported use in the past month (66% to 80%). Powder Cocaine and Methamphetamine followed in prevalence for rural areas, whereas Crack Cocaine and Methamphetamine characterized drug use in Omaha.

Despite similar patterns in drug use across sites, significant differences across rural sites and between rural sites and Omaha indicated that the level of use varied by location. Alcohol use was highest in Scotts Bluff (68%) for use in the past 3 days, but past 12 month Alcohol use was highest in Madison County (95%). In all categories, Alcohol use was the lowest in Hall/Dawson (77%). Arrestee use of powder Cocaine use was also highest in Scotts Bluff for use in the past 3 days and 30 days whereas it was the lowest in Madison. Although Crack use was extremely low in all rural areas, it appeared to exist in Hall/Dawson counties more often than Scotts Bluff and Madison. No significant differences were found in the use of Marijuana or Methamphetamine across rural areas. Compared to Omaha arrestees, rural arrestees were less likely to use any drug as much or more than Omaha except powder Cocaine and methamphetamine. The use of powder Cocaine was higher in rural sites than in Omaha, but the use of Methamphetamine was no different across locations.

The findings presented in Table 6 reinforce the variability of drug use by location and type of drug. Within rural sites comparisons, for instance, generated significant differences for Cocaine and Methamphetamine positives in Scotts Bluff and Hall/ Dawson Counties (respectively) compared to the other rural sites. Furthermore, positive urine results were significantly higher among Omaha arrestees than rural arrestees for every drug except methamphetamine.

As mentioned earlier, self reported Alcohol intoxication at the time of arrest was used as a proxy for chemical testing for alcohol. As shown in Table 6, rural arrestees were more likely to be intoxicated by Alcohol than other drugs at the time of arrest, but, in Omaha, the prevalence of Alcohol intoxication was similar to the prevalence of urine positives for any drug. Scotts Bluff arrestees were more likely to be intoxicated on Alcohol compared to other rural arrestees, but Alcohol intoxication was not significantly different between rural arrestees and Omaha arrestees overall.

COMPARING LOCATION WHILE CONTROLLING FOR ARRESTEE CHARACTERISTICS

Logistic regression was used to determine whether site differences would continue or disappear when arrestee characteristics (i.e., demographics, offense charges, and social information) were controlled. Table 7 contains the model results using self-reported Alcohol intoxication, positive for Marijuana, positive for "any drug" as dependent variables. As displayed in this table, Omaha arrestees were more likely to report Alcohol intoxication at the time of arrest and to test positive for any drug than arrestees in Madison and Hall/Dawson Counties, but neither model produced significant differences between Scotts Bluff and Omaha arrestees. For Marijuana, Omaha arrestees were more likely than Hall/Dawson arrestees to test positive but this likelihood was not significantly different between Scotts Bluff or Madison County arrestees and their Omaha counterparts.

The results for the control variables also warrant attention. According to the results contained in Table 7, male arrestees were significantly more likely to test positive for Marijuana than female arrestees; older arrestees were more likely to report Alcohol intoxication and to test positive for any type of drug than younger arrestees; and White arrestees were more likely to test positive for any type of drug compared to Black arrestees. With regard to offense type, arrestees charged with a drug offense were more likely to test positive for Marijuana and any type of drug than arrestees charged with a violent offense and more likely than property offenders to report Alcohol intoxication and test positive for Marijuana use. Marital status only impacted positive tests for marijuana: single and cohabitating arrestees were significantly more likely to test positive than their married counterparts.

DISCUSSION

The purpose of this study was to examine the prevalence of drug use among rural arrestees in Nebraska and compare these findings to those in Omaha, a more metropolitan area. Similar to previous ADAM findings, Alcohol and Marijuana were the most prevalent drugs for rural arrestees regardless of measurement method (i.e., self-report and urine results). Methamphetamine and powder Cocaine also played a role in rural arrestees drug use but the ranking of the two drugs depended on the measurement method. Using self-reports, rural arrestees reported using powder Cocaine more than Methamphetamine but urine results indicated that Methamphetamine was the second drug of choice in Madison and Hall/Dawson Counties. The findings for Scotts Bluff and Omaha were similar regardless of method. For Scotts Bluff, Cocaine was the second most prevalent drug and Methamphetamine was the third, and in Omaha, the use of Methamphetamine was preceded by Crack Cocaine use. Logistic regression analyses controlled for arrestee and offense characteristics and showed that Omaha arrestees were more likely to report Alcohol intoxication and test positive for Marijuana than arrestees in Hall/Dawson and Madison Counties, and more likely to report Marijuana use than arrestees in Hall/ Dawson County. Unfortunately, due to a low number of cases, logistic regression models could not be estimated for Methamphetamine or Cocaine use; however, the use of Methamphetamine and powder Cocaine was higher in rural areas using both self-reports and urine results. In sum, these findings showed that drug use is prevalent among rural arrestees and in some, cases, higher than metropolitan areas.

At least two conclusions surface from these findings. First, these results prove that drug use is prevalent among arrestees and discredits the notion that rural communities are immune to this particular problem. Between 30-45% of rural arrestees reported Alcohol intoxication at the time of arrest and 25-38% of rural arrestees tested positive for at least one drug at the time of arrest. Second, differences in drug use were more apparent across rural sites rather than between rural sites and Omaha, underscoring the importance of measuring "rural" carefully to capture differences between communities.

Explanations for the differences revealed in this study may include (1) geographical location, (2) availability of the drug, and (3) preference for a particular drug. With the exception of Madison County, the rural sites chosen for this study are located on Interstate 80, which is one of the major highways used to travel through the Midwest. The proximity of these sites to the highway provides a more direct connection to powder Cocaine (e.g., traveling from Denver to Omaha) than rural communities that are not located on a major highway. The nature of Crack markets (i.e., selling Crack on the street corner or a Crack house) is potentially less feasible due to the small nature of rural towns than in a metropolitan area. Conversely, Methamphetamine has historically played a role in rural areas due to the effects of the drug (i.e., assistance in working long hours on the farm or packaging plants), the ability to hide labs without detection, and easy access to the ingredients to make the drug (Travis & Vereen, 2000). Finally, the role of drugs may be connected to the demographics of an area. According to ADAM data, Methamphetamine use is more prevalent among White and Hispanic arrestees and Crack Cocaine use is more prevalent among Black arrestees. The demographics of the sites included in this study follow that pattern. Rural arrestees were predominately White and Hispanic whereas Omaha arrestees were predominately White and Black.

These results stress the need for more drug research and policy development in rural areas particularly since Alcohol and drug use potentially impacts rural areas in more significant ways than urban areas. Stereotypes surrounding the safety of rural communities are arguably based on the notion that rural communities are built on a tight web of informal controls and networks; yet, increasing crime and drug use may signify a weakening in the characteristics that insulated these areas in the past (Conger, 1997; Hobbs, 1994a). Neglecting these trends may also exacerbate the current problems associated with a lack of appropriate, quality substance abuse and dependency treatment in rural areas, such as a limited number of resources and services, lack of coordination and training, a shortage of staff, and long distances to travel (Modlin, Porter, & Benson, 1976; Leukefeld et al., 1992).

Despite these challenges, rural communities have a number of strengths that potentially help to effectively address drug use and crime such as size and personal resources. Because rural communities are small, the problems associated with drug use are more easily contained than in urban areas. Rural communities also define themselves in community terms rather than individualistic terms and consequently, have an abundance of personal resources at their disposal (see generally Conger, 1997; Edwards, 1993; Hobbs, 1994b). Rural communities, however, often lack the financial and technical resources that characterize urban areas. Thus, success in tackling the issues related to drug use and crime depend on several factors including:

Recognition and Documentation of the Problem at the Local Level: Perhaps the most important step in this process is recognizing the problem at the local level and mobilizing policy makers, courts, law enforcement and other criminal justice personnel, and treatment providers into action. Gathering statistics to document the problem strengthens this effort, educates the public, and enhances the community's ability to secure outside resources to address the problem. This step seems straightforward, but it often poses a tremendous hurdle because rural communities have traditionally relied on state systems, such as the Department of Corrections, to deal with the "problem." Unfortunately, this solution is short-lived because many offenders return to the communities with the same drug problems or in some cases, more problems.

Development and Implementation of an Infrastructure: Closely related to awareness is the community's need to create an infrastructure to support programming. Community leaders and policy-makers must work together to define the problem and gaps in the community, identify the community's priorities, create or adapt effective programming, and develop ways in which programming can flourish. In this capacity, rural areas often find themselves in a position where they must think and educate themselves about new issues and accept new directions for intervention.

Receptiveness to Innovative Programming: Innovative programs are currently in place throughout the nation to address issues related to drugs and crime within the community (e.g., drug courts) but the majority of these programs are implemented in more metropolitan areas. Although these programs may not apply to rural populations initially, rural communities interested in change can adapt effective programming to their community, especially if external assistance is available. The creation of the Central Nebraska Drug Court illustrates the feasibility of "tweaking" a program to "fit" rural communities. This program overlays several counties rather than one and utilizes county corrections in each area to regularly supervise participants often located long distances apart.

Commitment to Research and Evaluation: Once communities have implemented a plan to address drug use and crime, it is necessary to complete ongoing research and evaluation to ensure that their plan and programming is effective. By making such a commitment, communities can document the problem and their progress to compete for external resources and they can hold systems accountable for quality implementation of the community plan.

Of course, none of these actions will have significant impact unless state and federal officials recognize the problems facing rural communities, respect the policy needs and differences of rural areas, and accept innovative programming targeted toward the special needs of rural areas. Urban-based solutions and thinking will not automatically apply in rural areas; rather, local, state, and federal partnerships must work together to develop an infrastructure that builds on rural strengths, identity, and overall quality of life. Without such partnerships, the challenges currently facing rural communities will increasingly threaten the foundations of long-standing communities that play an important role in today's society.