2 and Purdue Pharma L.P. and which is now an independent operation of Denver Health & Hospital Authority, is a proactive surveillance program that monitors and charac- terizes the abuse and diversion of opioid pain medication [7]. 2. Methods 2.1. Sample. Data were collected from January 2005 through December 2009 from 23,141 enrollees in 84 OTPs located in 34 states. The number of study participants across the 84 OTPs ranged from 2 to 1,947 (median 155; quartile range: 71 to 372). Not all programs began study participation in January of 2005; 68 (81%) OTPs participated for 2 or more years; 12 (14%) participated for at least one year but less than two years; and 4 (5%) for less than one year. OTPs were selected primarily to represent regions in the USA where prescription opioid (PO) abuse was believed to be prevalent, for example, non-urban areas, especially those in the Appalachian region. Some OTPs were located in major metropolitan areas such as San Francisco and New York City, where PO abuse among OTP patients is believed to be relatively less prevalent. All programs were federally approved opioid agonist treatment programs and followed federal methadone treatment protocols that require an opioid-dependence diagnosis and an addiction history of at least 1 year [8]. The research protocol was approved by the Institutional Review Board of the National Development and Research Institutes, Inc. The respondents in this study include treatment seeking persons who reported abusing prescription opioids or heroin in the past 30 days and were not in methadone treatment in the previous 30 days. All patients enrolling in the study OTPs were targeted for recruitment. Several study procedures were implemented to maximize the number of OTP enrollees who participated. Patients were given an information sheet explaining the study’s rationale and procedures and that participation was voluntary and anonymous. Patients who completed the one- page survey instrument were compensated with a $5 food coupon. The OTPs were instructed to have patients complete the survey during the ﬁrst week of admission and to fax the surveys (along with a cover sheet that indicated the number of surveys included in the fax transmission) via a secure Internet-based fax service that forwarded the faxes to NDRI as an email attachment. (The faxed surveys were read by an automated form-driven data capture software program, Teleform Version 8.2, Verity, Inc., Sunnyvale, CA). In order to reinforce adherence to these procedures, each of the participating programs signed a letter of agreement that speciﬁed these study protocols and identiﬁed a liaison staﬀ person who served as the principal contact between the OTP and the study’s project director at the American Association for the Treatment of Opioid Dependence (AATOD; the organization responsible for communicating with the OTPs). The programs also received a stipend for their participation. Program participation was further reinforced by sending quarterly reports to each program of their data and an aggregate report of all study data. Further details of OTP participation and the subject recruitment protocol can be Journal of Environmental and Public Health found in a 2007 publication that described diﬀerences between prescription opioid users and heroin users [6]. 2.2. Variable Deﬁnitions. In order to assess travel distance and correlates associated with it, we utilized relevant data from the 1-page patient administered survey as well as program location information. Survey items addressed the following domains: demographics, treatment history, opioid use, drug craving, and pain; the survey also asked patients for their 5-digit ZIP code. Pain items were included because of the high prevalence of pain complaints among OTP patients [9, 10]. These measures are described below. 2.2.1. Travel Distance. The distance in miles between the center of the ZIP code of the patient’s residence and the street location of the OTP was used to represent patient travel distance. MapPoint (Microsoft Corp., Redmond, WA) was used to determine the centroid point of the patient’s residence ZIP code, the latitude/longitude of the OTP address, and the distance between these two locations. For statistical modeling, the natural logarithm of travel distance (with a constant of 1 added to all distances) was used. In order to avoid including subjects who may have written an incorrect ZIP code we excluded 266 patients who reported traveling more than two hundred miles to a treatment program. An examination of dispersion of the travel distance data showed that while distance was highly skewed to the right, the steepness of the decline precipitously dropped and remained at same level at approximately 200 miles. This pattern suggests that distances up to 200 miles were valid since they showed an expected pattern of fewer subjects with greater distance. 2.2.2. United States Region. OTPs were classiﬁed as falling into one of four USA regions. These regions, as designated by the U.S. Census Bureau [11], are Northeast (Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, Pennsylvania); Midwest (Ohio, Indiana, Illinois, Michigan, Wisconsin, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas); South (Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Oklahoma, Texas); West (Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada, Washington, Oregon, California, Alaska, Hawaii). 2.2.3. Beale Urbanicity Code. OTPs were in counties coded as high-density areas (population >1 million); moderately populated counties (≥250,000 and <1 million residents), and low populated counties (<250,000 residents); these three categories were determined by a modiﬁed version of the Beale Urbanicity Code [12]. The Beale code has 9 codes with 6 codes representing counties with <250,000 residents. Our previous research showed that a relatively small percent of respondents resided in the low populated counties; therefore we collapsed these 6 codes to reduce the skewness of the Beale distribution.