International Journal of Drug Policy - 2014

Volume 25 Issue 3 May 2014

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600 D. Kao et al. / International Journal of Drug Policy 25 (2014) 598–607 Methods Study location Houston, Texas is the fourth most populous city and third most populous county (Harris County) in the United States. The Houston metropolitan area has a population of approximately 5.8 million people (United States Census Bureau Population Division, 2010). Approximately half of the population in Houston and Har- ris County is Hispanic. Moreover, 73% of Hispanics in Houston and Harris County are of Mexican/Mexican American heritage (City of Houston Planning and Development Department, 2012). Recruitment for the current study focused on Southeast and North Houston, predominantly Mexican American areas with high rates of poverty and psychosocial strife. Both areas have high under- class characteristics, including the highest concentration of poverty (over 40%) in the city of Houston (City of Houston Planning and Development Department, 2004) and high rates of high school dropout, male unemployment, households receiving public assis- tance, and female-headed households (Valdez, Kaplan, & Curtis, 2007). These Mexican American communities tend to be socially isolated enclaves highly protective of its members and closed to individuals from other communities (Valdez, Neaigus, & Kaplan, 2008). Data and sample This study utilized data drawn from a National Institute on Drug Abuse study that examined health consequences of long- term injection heroin use in aging Mexican American men (Project CHIVA), conducted by the University of Houston's Center for Drug and Social Policy Research (CDSPR). The word "chiva" is an infor- mal or slang term for heroin in the Mexican American community. A field-intensive outreach methodology, executed by trained out- reach specialists who were familiar with the target communities, was employed to recruit a total of 227 Mexican American males aged 45 and older, who had injected heroin for at least 3 years during their lifetime. During the initial screening, individuals were categorized into three groups: former injectors not in treatment, former injectors enrolled in a methadone maintenance treatment program at the time of the interview, and current injectors. Semi- structured interviews were administered to the entire sample and in-depth follow-up ethnographic interviews were conducted with a subset of the sample. For this study, we utilized the quantita- tive data from the semi-structured interviews with the full sample. The study is further described in Torres, Kaplan, and Valdez (2011). The study protocol was approved by the University of Houston's Institutional Review Board (IRB). The analytic sample for this paper included 219 participants (out of the 227), who provided sufficient information (e.g. street address or cross streets) to allow us to geocode and map their approximate home residence at the time of the interview (Fig. 1). While recruit- ment of the sample was focused in Southeast and North Houston, as Fig. 1 shows, many participants lived in other parts of the city and Harris County. This study utilized two additional spatial data sources. First, information regarding outpatient substance abuse treatment facilities was obtained from the Substance Abuse and Mental Health Services Administration's (SAMHSA) Behavioral Health Treatment Services Locator web tool ( Based on where the participants lived, we included facilities located in the greater Houston area, particularly, Harris, Fort Bend, Brazoria, Montgomery, and Liberty counties. Locations of a total num- ber of 106 facilities—including 31 facilities providing services in Spanish—were geocoded (Fig. 2). Second, a street network is a special type of spatial data that includes streets, highways, and freeways (drawn as line features), but also includes key attributes associ- ated with those features, e.g. speed limits, one-way streets, dead ends, etc. Using Esri's StreetMap data (2006), spatial network anal- ysis was conducted to create the spatial accessibility measures discussed below. Measures Drug use-related outcomes Building on Jacobson's (2004) framework, this study focused on several outcomes related to drug use and treatment use. The par- ticipants' injection drug-related locus of control (LOC) was based on a series of six yes/no questions created specifically for this study: It is my own behavior, which determines whether I will inject drugs in the next 6 months; No matter what I do, if I'm going to inject drugs in the next 6 months, I will inject drugs in the next 6 months; I'm in control of whether or not I will inject drugs in the next 6 months; If I take the right actions, I can avoid injecting drugs in the next 6 months; I can change my drug use behaviors so that I do not inject drugs in the next 6 months; and No matter what I do, I am not likely to inject drugs in the next 6 months. The "no" responses were coded as 0 and the "yes" responses were coded as 1 (ques- tion 2 was reverse coded). We then computed a summative score ranging from 0 to 6 and dichotomized the sample into individuals with internal LOC (score of 4 or higher) and those with external LOC (score less than 4). Since this was a cross-sectional study, we relied on participants' self-reports in order to assess for the risk of future drug use. The participants' perceptions of the potential of injecting heroin in the future were measured by two 5-point Likert questions: the chances of injecting in the next six months; and how worried they were about injecting in the next six months. Based on the distribution of responses, the chances measure was dichotomized into "very high chance" versus "medium/low/very low/no chance" groups while the worried measure was dichotomized into "extremely/quite wor- ried" versus "somewhat/only a little/not at all worried" groups. Treatment use was represented by two measures: (1) whether the participant ever sought treatment (yes vs. no) and (2) whether the participant ever received treatment (yes vs. no). Finally, the location of last heroin purchase was a dichotomous measure, based on whether the participants made their last heroin purchase inside or outside the neighborhood. Spatial accessibility of treatment facilities Spatial network analyses, using Esri's Network Analyst (2011b) were used to derive two measures to operationalize the spatial accessibility of substance abuse treatment facilities: (1) distance to the closest facility (in minutes) and (2) number of facilities within a 10-minute driving distance (using any road combination). The clos- est facility tool was used to create the first measure. Participants who lived closer to a facility were considered to have greater spa- tial access to treatment than participants who live farther from a facility. For the second measure, the service area tool was used to compute a 10-minute "service area" for each participant—or the area representing at most a 10 minute drive from one's home, driv- ing in any direction and combination of roads. Once created, the number of facilities within each participant's service area was then counted. Both measures were calculated for all facilities and facil- ities also providing services in Spanish (to serve as a proxy for the provision of culturally competent services). Participants who lived in areas with more facilities were considered to have greater spatial access to treatment. The decision to use a 10-minute threshold was based on previous research looking at spatial accessibility from the health services research literature (Langford & Higgs, 2006), as well as research focused on food deserts (Jiao, Moudon,

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