Table 1.
Place-based constructs, variables studied and data sources
| Domain | Place construct | Variables (geographic scale) | Data source(s) |
|---|---|---|---|
| Sociodemographic composition | Availability of sex partners (male:female sex ratios) | Male:female sex ratio for adults (18–64 years; ZIP, county, MSA)a | 2010 Decennial Censusb,c |
| Racial/ethnic composition | Percent of total population who are non-Hispanic white, non-Hispanic black/African-American, or Hispanic/Latino (ZIP) | American Community Survey (ACS) 5-year Estimates (2007–2011)b | |
| Racial/ethnic residential segregation | Black isolation index (MSA)d | 2010 US Decennial Census | |
| Latino isolation index (MSA)d | 2010 US Decennial Census | ||
| Economic disadvantage | Exposure to economic disadvantage | Median household income (ZIP; county; MSA) | ACS 5-year Estimates (2007–2011)b |
| Percent of households below federal poverty line (ZIP; county; MSA) | ACS 5-year estimates (2007–2011)b | ||
| Percent of adults (≥ 16 years) in labor force who are unemployed (ZIP; county; MSA) | ACS 5-year estimates (2007–2011)b | ||
| Percent of adults (≥ 25 years) without a high school diploma or general equivalency diploma (ZIP; county; MSA) | ACS 5-year estimates (2007–2011)b | ||
| Income inequality | Gini coefficient (MSA) | 2010 Decennial Census | |
| Health and law enforcement interventions | Spatial access to substance use disorder treatment- and HIV-related programs | Density of HIV testing sites per square mile (ZIP) | Numerator (testing sites): CDC’s 2009 National HIV Prevention Program Monitoring & Evaluation database Denominator (square miles): US Census TIGER Filese This variable was dichotomized (0 vs. > 0) in analyses because of its skewed distribution |
| Spatial access to substance use disorder treatment programs, (a) overall; (b) methadone treatment programs (MTPs) and; (3) Syringe service programs (SSP) (ZIP) | Gravity-based methods were used to measure spatial access to treatment sites; data on treatment site location were available in SAMHSA’s National Directory of Drug and Alcohol Abuse Treatment Programs The MTP access variable was dichotomized (0 vs. > 0) in analyses because of its skewed distribution. |
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| Access to syringe service programs (SSP), (a) overall, and as classified by whether they (b) limit participants to one-for-one exchange, and (c) cap the number of syringes one can get in a single visit (ZIP) | Gravity-based methods were used to measure spatial access to treatment sites; data on treatment site location were available from Des Jarlais’ annual SSP survey This variable was dichotomized (0. vs. > 0) in analyses because of its skewed distribution. |
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| Access to general health care | Percent of adults (18–64 years) who are uninsured (county) | 2012–2013 Area Health Resource Filef | |
| Percent of residents living in a medically underserved area (county) | 2013 Health Professional Shortage Area Datasete | ||
| Exposure to law enforcement | Arrest rate for hard drug possessiong, per 1000 adults, by race/ethnicity (18–64 years; county, MSA) | Numerator (possession arrests by race/ethnicity): 2009 ICPSR county-level detailed arrest and offense data); Denominator (adults 18–64 years, by race/ethnicity): ACS 5-year estimates (2007–2011) | |
| Arrest rate for possession of any drug, per 1000 adults, by race/ethnicity (18–64 years; county, MSA) | Numerator (possession arrests, by race/ethnicity): 2009 ICPSR county-level detailed arrest and offense data Denominator (adults 18–64 years, by race/ethnicity): ACS 5-year estimates (2007–2011) |
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| Jail incarceration rate, per 1000 adults by race/ethnicity (18–64 years; MSA) | Numerator (jail inmates by race/ethnicity): 2010 Decennial census Denominator (adults 18–64 years by race/ethnicity): 2010 Decennial Census | ||
| Health and Law enforcement expenditures | Per capita expenditures on police (MSA) | Numerator (expenditures in USD): 2007 Census of Governments County Area Finances File | |
| Per capita expenditures on health (MSA) | Denominator (total population): US Census Bureau Population | ||
| Per capita expenditures on corrections (MSA) | Estimates Program | ||
| HIV burden | Loss of PWID population to AIDS during the HAART era | AIDS-related mortality rates for PWID during the HAART era, by race/ethnicity (MSA) | Numerator (total AIDS-related deaths from 1998–2008, by race/ethnicity): CDC Surveillance data; Denominator (total number of PWID in 1998, by race/ethnicity): CVAR studyh |
| AIDS diagnosis rates per PWID | AIDS diagnosis rates for PWID by race/ethnicity (MSA) | Numerator (total AIDS diagnosis from 1998–2008, by race/ethnicity): CDC Surveillance data; Denominator (total number of PWID in 1998, by race/ethnicity)h |
Male:female sex ratios were initially categorized into 3 levels: equal sex ratios (commonly defined as ranging from 0.95–1.05), more males (> 1.05), and more females (< 0.95); equity was used as the reference category to assess whether sex ratios were imbalanced. There were, however, no MSAs that had sex ratios indicating more males, thus in the end the measure included only 2 categories: more females and equity
People who were institutionalized (e.g., incarcerated) were excluded from calculations
When we used data from the Census Bureau to calculate ZIP-code level variables we used ZIP code tabulation areas instead of ZIP code areas. ZIP code tabulation areas are Census approximations of ZIP code areas
The isolation index measures the extent to which minority members are exposed only to one another, and was calculated per Massey and Denton [32]. The isolation index varies from 0 (no isolation) to 100 (complete isolation)
Topologically Integrated Geographic Encoding and Referencing system (TIGER) data, produced by the US Census Bureau. The TIGER/Line files are extracts of selected geographic information, including roads, boundaries, and hydrography features
This database contained historical data and so it was possible to capture conditions for 2009
Friedman et al. [19]. “Hard” drugs included opiates, cocaine, and “truly addicting” synthetic or other dangerous non-narcotic drugs
Tempalski et al. [34]