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Piloting a ‘Spatial Isolation’ Index : The Built Environment and Sexual and Drug Use Risks to Sex Workers Deering, Kathleen N.; Rusch, Melanie; Amram, Ofer; Chettiar, Jill; Nguyen, Paul; Feng, Cindy X.; Shannon, Kate May 31, 2014

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Piloting a ‘Spatial Isolation’ Index: The Built Environment andSexual and Drug Use Risks to Sex WorkersKathleen N Deering1,2, Melanie Rusch1,3, Ofer Amram1,4, Jill Chettiar1,5, Paul Nguyen1,Cindy X Feng6, and Kate Shannon1,2,51Gender and Sexual Health Initiative, BC Centre for Excellence in HIV/AIDS, St. Paul’s Hospital,Vancouver, Canada2Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada3Vancouver Island Health Authority, Victoria, Canada4Department of Geography, Faculty of Environment, Simon Fraser University, Burnaby, Canada5School of Population and Public Health, Faculty of Medicine, University of British Columbia,Vancouver, Canada6School of Public Health, Faculty of Medicine, University of Saskatchewan, Saskatoon, CanadaAbstractBackground—Employing innovative mapping and spatial analyses of individual andneighborhood environment data, we examined the social, physical and structural features ofoverlapping street-based sex work and drug scenes and explored the utility of a ‘spatial isolationindex’ in explaining exchanging sex for drugs and exchanging sex while high.Methods—Analyses drew on baseline interview and geographic data (Jan/10-Oct/11) from alarge prospective cohort of street and off-street sex workers (SWs) in Metropolitan Vancouver andexternal publically-available, neighborhood environment data. An index measuring ‘spatialisolation’ was developed from seven indicators measuring features of the built environment within50m buffers (e.g. industrial or commercial zoning, lighting) surrounding sex work environments.Bivariate and multivariable logistic regression was used to examine associations between the twooutcomes (exchanged sex for drugs; exchanged sex while high) and the index, as well as eachindividual indicator.© 2013 Elsevier B.V. All rights reserved.Corresponding author/ reprints: Kathleen N Deering, PhD, Postdoctoral Research Fellow, Canadian Institutes of Health Research(Bisby Award) & Michael Smith Foundation for Health Research, Division of AIDS, Faculty of Medicine, University of BritishColumbia; Analytic Research Coordinator, Gender and Sexual Health Initiative, British Columbia Centre for Excellence in HIV/AIDS, 608 - 1081 Burrard Street, Vancouver, BC, Canada V6Z 1Y6, gshi@cfenet.ubc.ca, Ph: 604-682-2344 (ext 66268), Fx:604-806-9044.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to ourcustomers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review ofthe resulting proof before it is published in its final citable form. Please note that during the production process errors may bediscovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Conflict of Interest StatementWe declare that we have no conflicts of interest including any financial, personal or other relationships with other people ororganizations within three years of beginning the submitted work that could inappropriately influence, or be perceived to influence,the submitted work.NIH Public AccessAuthor ManuscriptInt J Drug Policy. Author manuscript; available in PMC 2015 May 01.Published in final edited form as:Int J Drug Policy. 2014 May ; 25(3): 533–542. doi:10.1016/j.drugpo.2013.12.002.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptResults—Of 510 SWs, 328 worked in street-based/outdoor environments (e.g. streets, parks,alleys) and were included in the analyses. In multivariable analysis, increased spatial isolationsurrounding street-based/outdoor SWs’ main places of servicing clients as measured with theindex was significantly associated with exchanging sex for drugs. Exchanging sex for drugs wasalso significantly positively associated with an indicator of the built environment suggestinggreater spatial isolation (increased percent of parks) and negatively associated with thosesuggesting decreased spatial isolation (increased percent commercial areas, increased count oflighting, increased building footprint). Exchanging sex while high was negatively associated withincreased percent of commercial zones but this association was removed when adjusting for policeharassment.Conclusions—The results from our exploratory study highlight how built environment shapesrisks within overlapping street-based sex work and drug scenes through the development of anovel index comprised of multiple indicators of the built environment available through publiclyavailable data, This study informs the important role that spatially-oriented responses, such assafer-environment interventions, and structural responses, such as decriminalization of sex workcan play in improving the health, safety and well-being of SWs.Keywordssex workers; sex work; drug use; HIV risk; spatial analysisINTRODUCTIONIncreasing theoretical, qualitative and social epidemiological work has elucidated theimportant role of place, including the dynamic interplay between social context and physicaland structural environments, on influencing health risks experienced by vulnerable andmarginalized populations, including sex workers (SWs) and people who use drugs(Tempalski & McQuie, 2009). Rhodes’ ‘risk environment framework’ has been particularlyuseful in re-conceptualizing drug use harms, including drug-related harms, as beingproduced by social situations and places rather than solely by individual ‘risk behaviours’,with the ‘risk environment’ defined as the “space…in which a variety of factors interact toincrease the chances of drug-related harm” (Rhodes, 2002). Related research has advocatedfor conceptual and analytic methods that can account for the effects of social and physicalfactors operating on multiple and interrelated levels, including on the level of populations(macro), community (meso) and individual (micro) on HIV risk (Aral, Padian, & Holmes,2005; Diez Roux & Aiello, 2005; Rhodes, 2009). Further work by Blanchard and Aralconceptualizes sex work as a complex system, whereby the overlap of social context andphysical and structural environments of sex work interact to produce HIV risk; for example,in settings where sex work is highly criminalized and stigmatized, sex work environmentsremain largely hidden and isolated, highly mobile and controlled by pimps or brokers whoconnect SWs with clients (Blanchard & Aral, 2010).In settings where sex work and drug use markets overlap, place- and gender-based dual druguse and sexual risks for women may be exacerbated. The male-dominated nature of streetculture within such settings and the gendered dynamics of public spaces, wherein powerrelations favour male drug use and sexual partners, shape the negotiation of sexual practicesDeering et al. Page 2Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscript(Bourgois, Prince, & Moss, 2004; Rhodes, et al., 2012; Shannon, et al., 2008a). In suchsettings, sexual HIV transmission is thought to have been driven by the advent and increasein crack use since the early 1990s, the demands of which required women in particular totrade sex for drugs and negatively affected the amount of money for sex acts and power innegotiations with clients (Maher, 1997; Maher & Curtis, 1992; Maher, Dunlap, Johnson, &Hamid, 1996; Shannon, et al., 2008a). Limited research suggests that sex-for-drugexchanges are riskier than exchanging sex for money and have been associated with crackuse and unprotected sex and sex with a drug user (Kwiatkowski & Booth, 2000). SWs whoexchange sex for drugs or exchange sex while high are also less likely to be able to negotiateterms with clients (e.g., safer sex), more likely to engage in riskier sexual practices (e.g., sexwithout condoms, anal sex) in exchange for immediate drugs and less able to control thedrug preparation process (e.g., assess drug quality/safety, share drug use equipment assecond user) (Maher & Curtis, 1992; Maher, et al., 1996; Shannon, Kerr, Bright, Gibson, &Tyndall, 2008b).Key features of physical locations of sex work environments can play an important role ingender-based dual drug use and sexual risks to SWs, particularly in settings where sex workis criminalized. The geographic concentration of sex work in more hidden and isolatedspaces is often a “socially acceptable” strategy with the goal of removing the visiblepresence of sex work from the public eye (e.g., from streets, windows). Removing sex workfrom public spaces can happen explicitly through regulation (e.g. municipal zoningrestrictions on working in specific areas of a city) or through the creation of formal tolerancezones (e.g. ‘red light districts’) (Hubbard & Whowell, 2008; Lowman, 1992) or ‘defactotolerance zones’ due to local policing and fear of police harassment and arrest (Hubbard,1998). Spatial isolation of SWs, including through policing practices related to enforcementof sex work laws, has been associated with increased health harms to SWs, includinggender-based violence, risky sexual or drug-related behaviours (e.g., unsafe sex; sharingdrug use equipment) and lack of access to health services (Lazarus, Chettiar, Deering,Nabess, & Shannon, 2011; Rhodes, Simic, Baros, Platt, & Zikic, 2008; Shannon, et al.,2008a; Shannon, et al., 2009).This qualitative and social epidemiological research has been integral in identifying theimportance of features of place, including spatial isolation, on negative health risks amongSWs; however this research has largely relied on individual self-reported experiences anddescriptions of the individual’s environment. Critical work within the drug use and sexualhealth literature has examined the effects of social context and physical and structuralenvironments on health via aggregated or cumulative effects through indicators that measurefeatures of the built environment. The term ‘built environment’, has broad uses andapplications, and in our paper refers to features of human-made spaces, places orsurroundings in which human activity takes place. For example, the relationship betweenspatial access to sterile syringes, policing of drug use (arrests) and the use of safe drug useequipment has been assessed (Cooper, et al., 2012a; Cooper, et al., 2012b). An indexmeasuring the cumulative effects of physical disorder within neighbourhoods (e.g.,structural damage to homes; streets with trash, abandoned cars, graffiti; physical problemsand building code violations in high schools), the ‘Broken Window Index’, was examinedfor its influence on neighborhood gonorrhea rates in New Orleans (Cohen, et al., 2000).Deering et al. Page 3Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDespite important contributions of this work to understanding the effects of features ofplace, including within the built environment among marginalized and street-involvedpopulations, to date, there has been little to no cross-dialogue between built environmentresearch and spatial research of health inequities at the population level and qualitative andsocial epidemiological research of social and health harms at the individual level (e.g. cohortdata, qualitative in-depth interviews), particularly within sex work research.Through employing innovative mapping with a large cohort of SWs and spatial analyses ofboth individual data and neighbourhood environment data, our exploratory study aimed toaddress these gaps in research by examining the social, physical and structural features inoverlapping street-based sex work and drug scenes. Guided by existing theoretical,qualitative and social epidemiological research, we explored the utility of a spatial isolationindex of SWs’ built environment, and the relationship between this index and two dual druguse and sexual risk outcomes: exchanging sex while high and exchanging sex for drugs. Wealso examined the individual effects of built environment indicators that were used todevelop the index on the outcomes. In addition, given substantial evidence of the influenceof policing practices on influencing sex work activities as well as the spaces where sex workis practiced within settings where sex work is criminalized, we aimed to explore thepotential confounding effect of police harassment on the relationship between builtenvironment indicators and our two outcomes. This research is situated in Vancouver,Canada, a setting with criminalized policies toward both sex work (i.e., communicating/soliciting for the purposes of prostitution; owning and operating a brothel/bawdy house; andliving off the avails of prostitution) and drug use.METHODSSurvey design and sampleBeginning in January 2010, youth and adult women (14 years+) were enrolled in alongitudinal cohort known as ‘An Evaluation of Sex Worker’s Health Access’ (‘AESHA’).This study is based on substantial community collaborations (e.g., sex work agencies andservice providers) existing since 2005, and is monitored by a Community Advisory Boardwith representatives from 15+ agencies. Using time-location sampling,(Stueve, O'Donnell,Duran, San Doval, & Blome, 2001) women who exchanged sex for money within the last 30days (SWs) were recruited through outreach to outdoor sex work locations (i.e. streets,alleys), indoor sex work venues (i.e. massage parlours, micro-brothels, and in-call locations)and independent/self-advertising SWs (e.g. online, newspapers) in Metropolitan Vancouver.Our eligibility is inclusive of transgender individuals (male-to-female, MTF) who identify aswomen, based on our previous work (Shannon, 2007) and community guidance, as MTFtransgender individuals work in similar spaces as the female SW population, and access thesame services as the female SWs (directed toward self-identifying women, transgenderinclusive). Interviews were conducted in places where women felt comfortable (i.e., threeoffice site locations across Vancouver; within indoor sex work venues). As executedpreviously, outdoor sex work ‘strolls’ and indoor venues were identified through aparticipatory mapping exercise conducted with current/former SWs (Shannon, 2007), andcontinuously updated by the outreach team. The study holds ethical approval throughDeering et al. Page 4Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptProvidence Health Care/University of British Columbia Research Ethics Board. Allparticipants receive an honorarium of $40CAD at each bi-annual visit for their time,expertise and travel.Questionnaires and measuresFollowing informed consent, at baseline and each semi-annual follow-up visit, participantscompleted questionnaires by trained interviewers (both SW and non-SW interviewers) thatelicited responses relating to socio-demographics, sex work patterns/client experiences,work environments, occupational violence and interactions with policing, characteristics ofnon-commercial or regular partnerships, violence and trauma, and drug use. Participants alsocompleted a nurse-administered questionnaire that elicited responses relating to overallphysical, mental and emotional health, sexual and reproductive health and HIV testing andtreatment. As part of the nursing visit, SWs were also provided with extensive pre/and post-test counseling, testing for HIV, Hepatitis C Virus and sexually transmitted infections, andreferral for care and support services. Treatment was provided for symptomatic STIinfections by an on-site nurse, and free serology and Papanicolaou testing were alsoavailable for those in need, regardless of study enrollment.Study sampleOur study sample included SWs who solicited for or serviced clients primarily instreetbased/ outdoor settings. We considered only baseline data.OutcomesBased on a priori interest in examining overlapping drug use and sexual risks, we includedtwo sexual risk outcomes in this analysis, measured in the last six months: (1) exchangedsexual services directed for drugs (‘yes’=always, usually, sometimes, occasionally; versus‘no’=never); and (2) exchanged sexual services while high (‘yes’=always, usually,sometimes, occasionally; versus ‘no’=never).Potential confoundersWe considered the following potential confounders as measured once at baseline: age;reporting being a sexual minority (lesbian, gay, bisexual, transgender, transsexual, two-spiritversus heterosexual and non-transgender); Indigenous/Aboriginal ancestry (including FirstNations and Métis, Inuit status); migrant/new immigrant status (born outside Canada); andage at first sex work; as well as time-varying confounders updated in the last six months:homeless; had a manager; non-injection drug use; injection drug use; and numbers of clientsper week; and experienced police harassment without arrest (i.e., told to move on, threatenedwith arrest/detainment/fine, searched, followed, picked up and driven elsewhere to work,verbally harassed, detained, delayed/held against will without arrest, physically assaulted,drugs/drug use equipment taken, other property taken, propositioned to exchange sex,coerced into providing sexual favours).Deering et al. Page 5Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptSelection of built environment indicatorsWe used conceptual and analytic methods in the exploratory development of a ‘spatialisolation index’ within street-based/outdoor sex work environments, using seven variablesmeasuring different aspects of the built environment (Table 1). In the current study, the‘spatial isolation index’ and the term ‘spatial isolation’ in general is intended to reflect howsex work in our setting has been geographically concentrated in more hidden and isolatedspaces, away from the public eye (e.g., busy streets, residential areas) – research hassuggested that these spaces are moreover often further away from health resources (e.g.,harm reduction and safer sex equipment) and safety resources (e.g., groups of people, otherSWs, drop-in spaces, street-lights/busier commercial settings) (Shannon, et al., 2008a;Shannon, et al., 2009). To derive the seven individual built environment indicators for use indevelopment of an index, we used a combination of AESHA survey data and seven variablesmeasuring features of the built environment collected from publicly available data from theCity of Vancouver ("City of Vancouver Open Data Catalogue," 2013) and DTMI Spatial("DMTI Spatial Data and Services, " 2013). Little research is available on community-levelindicators of built environment and their relationships with health harms to street-basedSWs. As this study was exploratory in nature, we developed indicators that were suggestedby research to be important in shaping risk environments to SWs in street-based/outdoorsettings (Shannon, et al., 2008a; Shannon, et al., 2008c). From the AESHA data, we usedtwo variables measuring key spatial aspects of SWs’ work environments in the developmentof these indicators: locations of SWs’ main places of solicitation and main places whereservices were provided to clients, in the last six months. Locations were provided byparticipants in the form of addresses or cross-streets and geocoded (i.e., assigned latitudeand longitude). Using ArcGIS 10.1 ("ArcGIS Desktop," 2011), around each location, spatialbuffers were created. Effectively, ‘buffers’ are equivalent to a circle drawn around eachlocation as provided by participants. Each circle had an assigned radius of 50m, as we wereinterested in assessing the effects of built environment within a relatively near proximity toprimary sex work environments. These effects were perceived to be likely to have the largesteffect on SWs’ HIV risk. In line with previous work by our team (Rusch, et al., 2010;Shannon, et al., 2008c), confidentiality of participants’ individual responses was ensured asonly aggregate measures of sex work spaces were used in analysis. Neighbourhoodenvironment variables drawn from four different groups of external/publicly available datawere further used in the development of the index: road, lighting, building footprint and landuse ("City of Vancouver Open Data Catalogue," 2013; "DMTI Spatial Data and Services,"2013). These variables included, within each buffer, the: (1) sum of the length of majorroads; (2) sum of the length of alley roads; (3) percentage of commercial land use; (4)percentage of industrial land use; (5) percentage of parks; (6) number of light posts; and (7)percentage of the building footprint, or total built environment (i.e., coverage of land bycommercial buildings) (Table 1, Figure 1).Development of an index for 50m bufferWe drew on other studies that have developed indices of the built environment usingmultiple indicators of the built environment (e.g., neighbourhood disorder; street speedlimits, volume of cars, and street connectivity, walkability, land use, dwelling density)Deering et al. Page 6Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscript(Badland, et al., 2009; Cohen, et al., 2000; Kroeger, Messer, Edwards, & Miranda, 2012;McGinn, Evenson, Herring, Huston, & Rodriguez, 2007).Step 1: Conceptually, we hypothesized that greater major road length, greater percent ofcommercial land use and greater number of light posts was associated with decreased spatialisolation (as defined above), while greater length of alley roads, industrial land use andparks was associated with increased spatial isolation. Greater percent of building footprintcould be associated with increased spatial isolation or decreased spatial isolation (e.g.,building footprint could represent commercial buildings or industrial/abandoned, so theimpact of the overall footprint size would depend on type of building. These indicators wereconceptualized as described based on the previous work by Shannon et al (2008a; 2008c).These relationships were also validated from extensive discussion with project staff andcommunity members who are experts in understanding the experiences of the populationunder study.Step 2: For the seven items, we used simple correlations to determine the directions of itemsand how they were related to provide evidence to support out hypotheses. Results fromTable 2a (built environment indicators for place of solicitation) support our hypothesis,suggesting that major road length, percent commercial land use and number of lighting postswithin 50m buffers surrounding SWs’ main places of solicitation were positively correlated,while negatively correlated with alley road length, percent industrial land use and percentparks within 50m buffers. Interestingly, alley road length, percent industrial land use andpercent parks within 50m buffers were also negatively correlated with each other. Buildingfootprint was strongly negatively correlated with major road length (p<0.001) and positivelycorrelated with percent industrial land use (p<0.001), suggesting that it could be morestrongly associated with a measure of isolation. Results from correlations for builtenvironment indicators derived for 50m buffers surrounding SWs’ places of servicing clientswere identical to those derived for 50m buffers surrounding places of solicitation (Table 2b).Step 3: Based on our hypotheses and empirical analysis in Step 1 and Step 2, we thendeveloped an index or summary measure of the seven built environment indicators tomeasure ‘spatial isolation’ within street-based/outdoor sex work environments. Eachindicator was divided into deciles, with each of the ten deciles scored 1-10 or 10-1,depending on the hypothesized direction of association with spatial isolation. We assignedscores based on percentiles because indicators were measured with different units (i.e.,percent of industrial zoning versus number of light posts), to make indicators comparable.We validated the analysis using the index derived using quintiles (scored 1-5 or 5-1) andquartiles (scored 1-4 or 4-1).AnalysisBivariate and multivariable logistic regression was performed for the relationship betweenthe index and the two outcomes. Odds ratios were interpreted as follows: for each one-unitincrease in the index, the odds of the outcome increased/decreased by X%. We alsoperformed bivariate and multivariable logistic regression for the relationship between eachindividual built environment indicator and the two outcomes. Individual built environmentindicators were standardized for comparability, as we were interested in reporting theDeering et al. Page 7Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptdirection of association and its associated statistical significance rather than interpretingodds ratios. For completeness, odds ratios were reported for multivariable associations andinterpreted as follows: for each one-unit increase in the standardized built environmentindicator, the odds of the outcome increased/decreased by X%. We considered multivariablerelationships between individual built environment variables and the outcome when eachpair of variables was statistically significantly associated at a p<0.10-level, as this is pilotand exploratory analysis and we were interested in examining a broader number ofcomparisons. We hypothesized that increased spatial isolation (as measured by our index, aswell as by individual built environment indicators that comprise the index – describedbelow) will be associated with higher odds of exchanging sex while high and exchangingsex for drugs. As such, for each regression model, we used a confounder model approachusing the methods of Maldonado and Greenland (Maldonado & Greenland, 1993). Aspreviously (Lima, et al., 2008; Maldonado & Greenland, 1993), potential confounders wereselected for inclusion in the final models using a backward selection approach, whichconsidered the magnitude of change in the coefficient of the exposure variable. Starting witha fixed model, which considered all available variables, potential confounders were droppedone at a time, using the relative change in the coefficient for the variable related to theexposure variable as a criterion, until the maximum change from the full model exceeded5%. All analyses were performed using SAS software version 9.3 ("SAS Version 9.3,"2012).RESULTSCharacteristics of street-based/outdoor SWsOf 510 SWs within the AESHA cohort, 328 solicited for clients in primarily street-based/outdoor environments (e.g. streets, parks, alleys) and were included in the analyses, with amedian age of 34 years (Interquartile range: 29–43 years) and 45.5% (149) of Aboriginalancestry (First Nations, Metis, Inuit), 18.9% (62) reporting being a migrant/new immigrantand 23.5% (77) reporting being a sexual minority. Overall, 77.1% and 45.7% used non-injection and injection drugs in the last six months, respectively. In the last six months,70.7% (232) reported exchanging sex while high, while 32.6% (107) reported exchangingsex for drugs and 43.3% reported police harassment without arrest.Dual sexual and drug use-related risk and spatial isolation indexTable 3 presents bivariate associations between three derivations of the index (deciles,quintiles and quartiles) for place of soliciting and place of servicing clients and the outcomesmeasuring dual drug use and sexual risk (exchanging sex while high and exchanging sex fordrugs). Increased spatial isolation of SWs, as measured by our index, was strongly positivelyand significantly associated with both outcomes. These results were consistent across theindex derived using deciles, quintiles and quartiles, and for buffers surrounding SWs’ mainplaces of solicitation and of servicing clients.Table 4 presents multivariable associations between three derivations of the index (deciles,quintiles and quartiles) for place of soliciting and place of servicing clients and exchangingsex while high and exchanging sex for drugs. In multivariable analysis, after adjusting forDeering et al. Page 8Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptkey confounders, exchanging sex for drugs remained positively and significantly associatedwith the index measuring spatial isolation of SWs, for the index derived for SWs’ mainplace of servicing clients and for deciles (AOR: 1.03, 95%CIs: 1.00–1.05), quintiles (AOR:1.06, 95%CIs: 1.01–1.10) and quartiles (AOR: 1.09, 95%CIs: 1.02–1.16).Dual sexual and drug use-related risk, police harassment and built environment indicatorsIn bivariate analysis, for individual built environment indicators, as derived for 50m bufferaround SWs’ main place of solicitation, exchanging sex while high was significantlyassociated with the following indicators on a p<0.10-level: length of major roads (0.024);percent commercial zoning (P=0.006); percent industrial zoning (P=0.048); and percentparks (P=0.077). Exchanging sex for drugs was significantly associated with: length ofmajor roads (P=0.057); and percent parks (P=0.008). In bivariate analysis, for individualbuilt environment indicators, as derived for 50m buffer around SWs’ main place ofservicing, exchanging sex while high was significantly associated with the followingindicators on a p<0.10-level: length of alleys (<0.001); percent commercial zoning (0.063);percent industrial zoning (0.026); percent parks (0.074). Exchanging sex for drugs wassignificantly associated with: length of major roads (0.071); percent commercial zoning(0.005); percent parks (0.001); number of light posts (0.022); and percent building footprint(0.033).Tables 5a and 6a present multivariable relationships between individual built environmentindicators and these two outcomes, developed for buffers surrounding places of solicitationand servicing, respectively. Tables 5b and 6b presents the same analysis, with themultivariable models for the two outcomes adjusted for police harassment. For the buffersdeveloped surrounding places of solicitation, in multivariable analysis, reduced odds ofexchanging sex while high (AOR: 0.76, 95%CIs: 0.59–0.99) were significantly associatedwith increased percent of commercial areas. Elevated odds of exchanging sex for drugs wereassociated with increased percent of parks (AOR: 1.36, 05%CIs: 1.06–1.75) (Table 5a). Forthe models where police harassment was identified as a key confounder, after adjusting forpolice harassment, the significant association between exchanging sex while high andincreased percent of commercial areas was removed, but the association betweenexchanging sex for drugs and increased percent of parks remained (AOR: 1.38, 95%CIs:1.07–1.78) (Table 5b).For the buffers developed surrounding places of servicing, in multivariable analysis, reducedodds of exchanging sex while high (AOR: 0.69, 95%CIs: 0.53–0.89) were significantlyassociated with increased length of alleys. Reduced odds of exchanging sex for drugs wereassociated with increased percent of commercial zoning (AOR: 0.72, 95%CIs: 0.57–0.92),increased count of lighting (AOR: 0.73, 95%CIs: 0.56–0.93) and increased percent ofbuilding footprint (AOR: 0.75, 95%CIs: 0.60–0.95). Elevated odds of exchanging sex fordrugs were significantly associated with increased percent of parks (AOR: 1.58, 95%CIs:1.14–2.18) (Table 6a). For the relationships where police harassment was identified as a keyconfounder, the association between exchanging sex for drugs and increased percent ofparks (AOR: 0.74, 95%CIs: 0.58–0.93) and increased building footprint (AOR: 0.76,95%CIs: 0.60–0.97) remained (Table 6b).Deering et al. Page 9Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptCONCLUSIONSNovel social epidemiological and spatial methods that integrate neighbourhood environmentand individual level data can help us understand how social, physical and structure featuresof place shape potential health harms for marginalized populations. In particular, ourexploratory research suggests that a ‘spatial isolation’ index within street-based sex workscenes can help illuminate how physical and structural features of the built environment mayincrease dual drug use and sexual risks, and inform policy and interventions.We hypothesized that each built environment indicator represented a measure of ‘spatialisolation’ from some service or resource that is important in contributing toward reducingnegative health outcomes among SWs (e.g., health services, safer sex and drug equipmentresources and personal safety resources), and that increased spatial isolation would beassociated with increased vulnerability to health harms as represented by increased sex-for-drug exchanges and exchanging sex while high. In developing our index, we were unable tovalidate externally that our index measured what we intended it to and were limited byavailability of variables in external databases. However, our results were in the direction wewould expect based on previous research and in line with our hypotheses. Increased spatialisolation surrounding street-based/outdoor SWs’ main places of servicing clients, asmeasured with an index that took into account the effects of multiple built environmentindicators and was intended to provide an overall measure of SWs’ spatial isolation fromresources and services, was significantly associated with exchanging sex for drugs. Whenassessed individually in multivariable analysis for built environment indicators surroundingSWs’ main places of solicitation and servicing, elevated odds of sex-for-drug exchangeswere significantly associated with an indicator of the built environment hypothesized to beassociated with greater spatial isolation (increased percent of parks). Moreover, reducedodds of sex-for-drug exchanges were significantly associated with built environmentindicators surrounding SWs’ main places of servicing hypothesized to be associated withdecreased spatial isolation (increased percent commercial areas, increased count of lighting,increased building footprint).Given evidence highlighting the connections between police harassment of SWs and spatialisolation of SWs to places further away from public spaces and commercial areas, as well asaway from places where health and harm reduction services are accessed (Hubbard, 1998;Lowman, 1992, 2000) (Kerr & Wood, 2005; Shannon, et al., 2008a; Shannon, et al., 2008c),our index can be viewed as a potential marker for such policing practices, in addition to itsmore direct interpretation as an overall representation of isolation from resources andservices. This observation is supported by results (not shown) suggesting bivariaterelationships between reduced police harassment without arrest and increased: percentcommercial zoning (P=0.001); number of light posts (P=0.032); and percent buildingfootprint (P=0.089) (i.e., markers of spatial isolation). Heavier police presence has beenassociated with increased risk for transmission of blood-borne or sexually transmittedinfections to SWs and drug users through a number of spatial pathways; for example,heavier arrest rates have negatively affected the association between increased spatial accessto sterile syringes and the use of safe drug use equipment (Cooper, et al., 2012a; Cooper, etal., 2012b); increased police presence and previous arrests/harassment by police have beenDeering et al. Page 10Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptassociated with rushed negotiations with clients or rushed and unsafe drug use, injecting anddoing sex work in unsafe spaces and having safer sex and drug use equipment confiscated(Kerr & Wood, 2005; Shannon, et al., 2008a; Small, Kerr, Charette, Schechter, & Spittal,2006); and being able to access safer indoor drug use spaces has alleviated the pressures ofpolicing and violence in public drug use spaces and facilitated use of safer drug useequipment (Fairbairn, Small, Shannon, Wood, & Kerr, 2008). Such research helps explainour association between increased spatial isolation as measured by our index andexchanging sex for drugs. Moreover, our results showed that without adjusting for policeharassment, working in areas with increased percent of commercial zones was associatedwith reduced risk for exchanging sex while high; however in multivariable analysis, thisassociation was removed when adjusting for police harassment, which was identified as akey confounder in this relationship and had the strongest association with exchanging sexwhile high (5.7-fold elevated odds) relative to other confounders.Spatial and place-based research on risk environments are critical to health policy as studyresults “can locate precisely places of potential risk environments, social vulnerability andwhere structural interventions are urgently needed” (Tempalski & McQuie, 2009). Giventhat our results indicate that SWs with dual drug use and sexual risks may be at heightenedrisk of spatial isolation that could enhance their risks our study suggests a number of policyimplications that are spatially oriented. Research suggests that development and scale-up ofsafer environment interventions (e.g., mobile outreach (Deering, et al., 2011; Janssen,Gibson, Bowen, Spittal, & Petersen, 2009)) that modify the physical environments of street-based/outdoor SWs can be instrumental in reducing sexual and drug-related harms. Inaddition, in line with global calls (Ahmed, Kaplan, Symington, & Kismodi, 2011; Nosyk &Wood, 2012; Shannon, 2010; Shannon & Csete, 2010; Wood, McKinnon, Strang, &Kendall, 2012),, there is strong evidence and global policy support (e.g.,: WHO/UNguidelines, Global Commission for HIV and the Law) for decriminalization ofcommunicating for purposes of sex work in public/outdoor spaces (‘communicating code’)to ensure access to safer indoor spaces for sex work with supportive policies (e.g.,occupational health and safety standards, supportive and safer policies toward drug use) thatsupport SWs ability to better control sexual transactions and reduce health harms to SWs(Shahmanesh, Patel, Mabey, & Cowan, 2008)).(Ghose, Swendeman, & George, 2011;Kerrigan, et al., 2003; Krusi, et al., 2012; Withers, Dornig, & Morisky, 2007). The shiftaway from policing tactics toward street-based/outdoor sex work that result in sex workspaces being moved into areas where there is limited access to health and safety resourcescould increase dialogue between SWs and police and contribute to the development ofstreet-based/public sex work spaces that satisfy the needs of SWs along with communityresidents. In such cases, it may be possible that police presence could have a positive impacton SWs’ sexual and drug-related risk. Safer-environment interventions would also befacilitated in a decriminalized environment, but are critical in a criminalized environment,particularly when places of sex work solicitation and servicing are known to be in areaswhere SWs are less able to access health and safety resources.This study had a number of strengths as well as limitations that should be taken into accountwhen interpreting results. Since sampling frames are difficult to construct for hiddenpopulations, the sample was not randomly generated and may not be representative of allDeering et al. Page 11Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptstreet-based/ outdoor SWs in ours or other settings. To address this, we recruited participantsthrough systematic time-location sampling and targeted outreach to sex work strolls andindoor locations (Stueve, et al., 2001), considered the best method of recruitment for mobile/hidden populations and therefore helping attract a representative sample. The study design iscross-sectional in nature and thus cannot determine causal relationships between spatialisolation and increased sexual and drug use risks to sex workers. As with all self-report data,responses may be subject to recall or social desirability bias. To counteract these potentialbiases, we had extensively trained interviewers with experience with the sample population,and interviews were conducted in spaces where women were comfortable (i.e., indoor workplaces), facilitating accurate responses. As discussed above, there is growing researchsuggesting that spatial isolation (e.g., through policing practices) can result in sex workersexperiencing heightened health risks through sexual and drug injection routes. Fewprospective studies with sex workers have been conducted, however, limiting the strength ofconclusions regarding these relationships; our study points to areas where such research isneeded.There are some specific limitations with respect to the development of the index. Forexample, one limitation of the indicators used to develop our index is related to temporality.The relative ‘spatial isolation’ of a particular feature of the built environment (e.g.,percentage of parks, number of streetlights) may differ according to the time of day/night.For example, the impact of reduced number of streetlights will be different for sex workerswho work daytime hours than those who work nighttime hours. We were unable to accountfor the exact times at which SWs work. In our study setting, however, where sex work iscriminalized, the majority of street-based sex work occurs during nighttime hours in order toavoid enforcement of sex work laws governing public solicitation; during nighttime hours,the impacts of various features of the built environment are likely to be relatively consistent.Our index measuring spatial isolation was moreover derived using external environmentaldata on built environment rather than individual-level self-report data. The intent of usingdata external to individuals was to remove subjective interpretations of environments onrisk, which has been shown to have poor agreement with ‘objective’ indicators of builtenvironments (McGinn, et al., 2007).In summary, the results from our exploratory study highlight how built environment shapesrisks within overlapping street-based sex work and drug scenes through the development ofa novel index comprised of multiple indicators of the built environment available throughpublicly available data. The process through which this index was developed and the indexitself can be used as a key starting point from which to build on to better understand therelationship between built environment and drug use and sexual risk to SWs in Vancouverand other settings. Indicators that are setting-specific should be chosen for specific settings.We have demonstrated that publicly available spatial data can be very useful in providing anexternal viewpoint of the relationships between space, place and risk to sex workers, andprovides unique insights that cannot be gained from self-report data alone. However, thecomplex and multi-level nature of these relationships would benefit from furtherdevelopments to the index, including incorporating data from multiple sources andmethodologies, such as ethnographic and qualitative assessments, quantitative survey dataDeering et al. Page 12Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptalongside external data. This study informs the important role that spatially-oriented andstructural responses can play in improving the health, safety and well-being of SWs.AcknowledgmentsWe thank all those who contributed their time and expertise to this project, including participants, partner agenciesand the AESHA Community Advisory Board. We wish to acknowledge Peter Vann, Gina Willis, Annick Simo,Ofer Amram, Paul Nguyen, Sabina Dobrer, Jill Chettiar, Jennifer Morris, Alex Scot and Kathleen Deering for theirresearch and administrative support. This research was supported by operating grants from the US NationalInstitutes of Health (R01DA028648) and Canadian Institutes of Health Research (HHP-98835). KND is supportedby Postdoctoral Fellowships from the Canadian Institutes of Health Research (Bisby Award) and the Michael SmithFoundation for Health Research. KS is supported by US National Institutes of Health (R01DA028648), CanadianInstitutes of Health Research and Michael Smith Foundation for Health Research.REFERENCESAhmed A, Kaplan M, Symington A, Kismodi E. Criminalising consensual sexual behaviour in thecontext of HIV: Consequences, evidence, and leadership. Global Public Health. 2011; 6:S357–S369. [PubMed: 22050481]Aral SO, Padian NS, Holmes KK. Advances in multilevel approaches to understanding theepidemiology and prevention of sexually transmitted infections and HIV: an overview. Journal ofInfectious Diseases. 2005; 191:S1–S6. [PubMed: 15627219]ArcGIS Desktop. Release 10 ed. Redlands, CA, USA: Environmental Systems Research Institute;2011.Badland H, Schofield G, Witten K, Schluter P, Mavoa S, Kearns R, Hinckson E, Oliver M, Kaiwai H,Jensen V, Ergler C, McGrath L, McPhee J. Understanding the Relationship between Activity andNeighbourhoods (URBAN) Study: research design and methodology. BMC Public Health. 2009;9:224. [PubMed: 19589175]Blanchard JF, Aral SO. Emergent properties and structural patterns in sexually transmitted infectionand HIV research. Sexually Transmitted Infections. 2010; 86:iii4–iii9. [PubMed: 21098056]Bourgois P, Prince B, Moss A. The Everyday Violence of Hepatitis C Among Young Women WhoInject Drugs in San Francisco. Hum Organ. 2004; 63:253–264. [PubMed: 16685288]City of Vancouver Open Data Catalogue. [Retrieved January 1 2012] from http://data.vancouver.ca/datacatalogue/index.htm.Cohen D, Spear S, Scribner R, Kissinger P, Mason K, Wildgen J. "Broken windows" and the risk ofgonorrhea. Am J Public Health. 2000; 90:230–236. [PubMed: 10667184]Cooper H, Des Jarlais D, Ross Z, Tempalski B, Bossak B, Friedman S. Spatial Access to SterileSyringes and the Odds of Injecting with an Unsterile Syringe among Injectors: A LongitudinalMultilevel Study. Journal of Urban Health. 2012a; 89:678–696. [PubMed: 22585448]Cooper HLF, Des Jarlais DC, Tempalski B, Bossak BH, Ross Z, Friedman SR. Drug-related arrestrates and spatial access to syringe exchange programs in New York City health districts:Combined effects on the risk of injection-related infections among injectors. Health &amp; Place.2012b; 18:218–228. [PubMed: 22047790]Deering KN, Kerr T, Tyndall MW, Montaner JSG, Gibson K, Irons L, Shannon K. A peer-led mobileoutreach program and increased utilization of detoxification and residential drug treatment amongfemale sex workers who use drugs in a Canadian setting. Drug and Alcohol Dependence. 2011;113:46–54. [PubMed: 20727683]Diez Roux AV, Aiello AE. Multilevel Analysis of Infectious Diseases. Journal of Infectious Diseases.2005; 191:S25–S33. [PubMed: 15627228]DMTI Spatial Data and Services. [Retrieved January 31 2012] from http://www.dmtispatial.com/.Fairbairn N, Small W, Shannon K, Wood E, Kerr T. Seeking refuge from violence in street-based drugscenes: Women's experiences in North America's first supervised injection facility. Social Science& Medicine. 2008; 67:817–823. [PubMed: 18562065]Ghose T, Swendeman DT, George SM. The Role of Brothels in Reducing HIV Risk in Sonagachi,India. Qual Health Res. 2011; 21:587–600. [PubMed: 21266706]Deering et al. Page 13Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptHubbard P. Community action and the displacement of street prostitution: evidence from British cities.Geoforum. 1998; 29:269–286.Hubbard P, Whowell M. Revisiting the red light district: Still neglected, immoral and marginal?Geoforum. 2008; 39:1743–1755.Janssen PA, Gibson K, Bowen R, Spittal PM, Petersen KL. Peer support using a mobile access vanpromotes safety and harm reduction strategies among sex trade workers in Vancouver’s downtowneastside. Journal of Urban Health. 2009; 86:804–809. [PubMed: 19533367]Kerr T, Wood E. The public health and social impacts of drug market enforcement: A review of theevidence. Int J Drug Pol. 2005; 16:210–220.Kerrigan D, Ellen JM, Moreno L, Rosario S, Katz J, Celentano DD, Sweat M. Environmental-structural factors significantly associated with consistent condom use among female sex workersin the Dominican Republic. AIDS. 2003; 17:415–423. [PubMed: 12556696]Kroeger GL, Messer L, Edwards SE, Miranda ML. A novel tool for assessing and summarizing thebuilt environment. Int J Health Geogr. 2012; 11:46. [PubMed: 23075269]Krusi A, Chettiar J, Ridgway A, Abbott J, Strathdee SA, Shannon K. Negotiating Safety and SexualRisk Reduction With Clients in Unsanctioned Safer Indoor Sex Work Environments: A QualitativeStudy. American Journal of Public Health. 2012; 102:1154–1159. [PubMed: 22571708]Kwiatkowski C, Booth R. Differences in HIV Risk Behaviors Among Women Who Exchange Sex forDrugs, Money, or Both Drugs and Money. AIDS and Behavior. 2000; 4:233–240.Lazarus L, Chettiar J, Deering K, Nabess R, Shannon K. Risky health environments: Women sexworkers’ struggles to find safe, secure and non-exploitative housing in Canada’s poorest postalcode. Social Science & Medicine. 2011; 73:1600–1607. [PubMed: 22018526]Lima VD, Harrigan R, Murray M, Moore DM, Wood E, Hogg RS, Montaner JS. Differential impact ofadherence on long-term treatment response among naive HIV-infected individuals. AIDS. 2008;22:2371–2380. 2310.1097/QAD.2370b2013e328315cdd328313. [PubMed: 18981777]Lowman J. Street prostitution control: some Canadian reflections on the Finsbury Park experience.British Journal of Criminology. 1992; 32Lowman J. Violence and the Outlaw Status of (Street) Prostitution in Canada. Violence AgainstWomen. 2000; 6:987–1011.Maher, L. Sexed work: Gender, race and resistance in a Brooklyn drug market. New York: OxfordUniversity Press; 1997.Maher L, Curtis R. Women on the edge of crime: Crack cocaine and the changing contexts of street-level sex work in New York City. Crime, Law and Social Change. 1992; 18:221–258.Maher L, Dunlap E, Johnson BD, Hamid A. Gender, power, and alternative living arrangements in theinner-city crack culture. Journal of Research in Crime and Delinquency. 1996; 33:181–205.Maldonado G, Greenland S. Simulation Study of Confounder-Selection Strategies. American Journalof Epidemiology. 1993; 138:923–936. [PubMed: 8256780]McGinn AP, Evenson KR, Herring AH, Huston SL, Rodriguez DA. Exploring Associations betweenPhysical Activity and Perceived and Objective Measures of the Built Environment. J UrbanHealth. 2007; 84:162–184. [PubMed: 17273926]Nosyk B, Wood E. Evidence-based drug policy: It starts with good evidence and ends with policyreform. The International journal on drug policy. 2012; 23:423–425. [PubMed: 23159128]Rhodes T. The 'risk environment': a framework for understanding and reducing drug-related harm.International Journal of Drug Policy. 2002; 13:85–94.Rhodes T. Risk environments and drug harms: a social science for harm reduction approach. Int J DrugPolicy. 2009; 20:193–201. [PubMed: 19147339]Rhodes T, Simic M, Baros S, Platt L, Zikic B. Police violence and sexual risk among female andtransvestite sex workers in Serbia: qualitative study. BMJ. 2008; Vol. 337:a811. [PubMed:18667468]Rhodes, T.; Wagner, K.; Strathdee, S.; Shannon, K.; Davidson, P.; Bourgois, P. Structural Violenceand Structural Vulnerability Within the Risk Environment: Theoretical and MethodologicalPerspectives for a Social Epidemiology of HIV Risk Among Injection Drug Users and SexWorkers. In: O’Campo, P.; Dunn, JR., editors. Rethinking Social Epidemiology. Netherlands:Springer; 2012. p. 205-230.Deering et al. Page 14Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptRusch MLA, Brouwer KC, Lozada R, Strathdee SA, Magis-RodrÃguez C, Patterson TL. Distributionof Sexually Transmitted Diseases and Risk Factors by Work Locations Among Female SexWorkers in Tijuana, Mexico. Sexually Transmitted Diseases. 2010; 37:608–614. [PubMed:20585278]SAS Version 9.3. Cary, USA: SAS Institute Inc; 2012.Shahmanesh M, Patel V, Mabey D, Cowan F. Effectiveness of interventions for the prevention of HIVand other sexually transmitted infections in female sex workers in resource poor setting: asystematic review. Tropical Medicine & International Health. 2008; 13:659–679. [PubMed:18266784]Shannon K. The hypocrisy of Canada’s prostitution legislation. CMAJ. 2010; 182:1388. [PubMed:20713573]Shannon K, Bright V, Parsad D, Alexson D, Allinott S, Gibson K, Tyndall MW. Community-BasedHIV prevention research among substance-using women in survival sex work: The Maka Project.Harm Reduction Journal. 2007:20–26. [PubMed: 18067670]Shannon K, Csete J. Violence, Condom Negotiation, and HIV/STI Risk Among Sex Workers. JAMA:The Journal of the American Medical Association. 2010; 304:573–574. [PubMed: 20682941]Shannon K, Kerr T, Allinott S, Chettiar J, Shoveller J, Tyndall MW. Social and structural violence andpower relations in mitigating HIV risk of drug-using women in survival sex work. Social Scienceand Medicine. 2008a; 66:911–921. [PubMed: 18155336]Shannon K, Kerr T, Bright V, Gibson K, Tyndall MW. Drug sharing with clients as a risk marker forincreased violence and sexual and drug-related harms among survival sex workers. AIDS Care.2008b; 20:235–241. [PubMed: 18293135]Shannon K, Kerr T, Strathdee SA, Shoveller J, Montaner JS, Tyndall MW. Prevalence and structuralcorrelates of gender based violence among a prospective cohort of female sex workers. BMJ.2009; 339:b2939. [PubMed: 19671935]Shannon K, Rusch M, Shoveller J, Alexson D, Gibson K, Tyndall MW. Mapping violence andpolicing as an environmental-structural barrier to health service and syringe availability amongsubstance-using women in street-level sex work. Int J Drug Policy. 2008c; 19:140–147. [PubMed:18207725]Small W, Kerr T, Charette J, Schechter MT, Spittal PM. Impacts of intensified police activity oninjection drug users: Evidence from an ethnographic investigation. International Journal of DrugPolicy. 2006; 17:85–95.Stueve A, O'Donnell LN, Duran R, San Doval A, Blome J. Time-Space Sampling in MinorityCommunities: Results With Young Latino Men Who Have Sex With Men. Am J Public Health.2001; 91:922–926. [PubMed: 11392935]Tempalski B, McQuie H. Drugscapes and the role of place and space in injection drug use-related HIVrisk environments. The International journal on drug policy. 2009; 20:4–13. [PubMed: 18554896]Withers M, Dornig K, Morisky DE. Predictors of workplace sexual health policy at sex workestablishments in the Philippines. AIDS Care. 2007; 19:1020–1025. [PubMed: 17851999]Wood E, McKinnon M, Strang R, Kendall PR. Improving community health and safety in Canadathrough evidence-based policies on illegal drugs. Open Medicine. 2012; 6:e35–e40. [PubMed:22567081]Deering et al. Page 15Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptFigure 1.Representation of how built environment indicators were derived (not an actual map ofVancouver); black dot represents sex workers’ main place of solicitation or servicing clients,with black circles representing different potential buffer sizes (the current study used 50mbuffers); green squares represent parks; red squares represent commercial zoning; lightgreen areas represent industrial zoning; yellow areas represent building footprint; red dotsDeering et al. Page 16Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author Manuscriptrepresent light posts. Descriptions of seven derived built environment indicators are in Table1.Deering et al. Page 17Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 18Table 1Indicators of the built environment, developed for a buffer size of 50mGroup Description Variable SourceRoads Sum of road length within a buffer Major Roads DMTIAlley Roads City of VancouverLand Use % of land use of total buffer area Commercial DMTIIndustrial DMTIParks DMTILighting Number of light posts within a buffer Lighting City of VancouverBuilding Footprint % of building footprint of total buffer area Building footprint City of VancouverInt J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 19Table 2a. Correlations between seven built environment indicators, using place of solicitation(50m buffers)MajorroadlengthAlleyroadlength%Commercial%Industrial%ParksLightpostsBuildingfootprintMajor roadlength1.000Alley roadlength−0.260P=0.0001.000% Commercial0.472P=0.0000.068P=0.2221.000% Industrial−0.217P=0.001−0.092P=0.097−0.302P=0.0001.000% Parks−0.338P=0.000−0.0320.560−0.356P=0.000−0.279P=0.0001.000Light posts0.610P=0.000−0.068P=0.2210.550P=0.000−0.380P=0.000−0.173P=0.0021.000Buildingfootprint−0.465P=0.0000.027P=0.6260.060P=0.2830.352P=0.000−0.100P=0.069−0.327P=0.0001.000b. Correlations between seven built environment indicators, using place of servicing(50m buffers)MajorroadlengthAlleyroadlength%Commercial%Industrial%ParksLightpostsBuildingfootprintMajor roadlength1.000Alley roadlength−0.172P=0.0011.000% Commercial0.393P=0.000−0.036P=0.4971.000% Industrial−0.132P=0.011−0.072P=0.169−0.158P=0.0021.000% Parks−0.287P=0.0000.121P=0.020−0.284P=0.000−0.248P=0.0001.000Light posts0.460P=0.000−0.049P=0.3480.596P=0.000−0.235P=0.000−0.098P=0.0591.000Buildingfootprint−0.267P=0.000−0.073P=0.1650.339P=0.0000.199P=0.000−0.139P=0.0080.104P=0.0471.000Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 20Table 3Bivariate associations between three derivations of the index (deciles, quintiles and quartiles) for place of soliciting and place of servicing clients andexchanging sex while high and exchanging sex for drugsExchanging sex while highExchanging sex for drugsORs [95%CIs]PORs [95%CIs]PPlace ofsolicitationDeciles1.04 [1.02–1.06]<0.0011.02 [1.00–1.04]0.034Quintiles1.08 [1.03–1.12]<0.0011.04 [1.00–1.08]0.037Quartiles1.11 [1.05–1.18]<0.0011.06 [1.01–1.12]0.034Place ofservicingclientsDeciles1.03 [1.01–1.05]0.0121.03 [1.01–1.05]0.007Quintiles1.05 [1.01–1.10]0.0211.06 [1.01–1.10]0.011Quartiles1.08 [1.01–1.14]0.0201.09 [1.03–1.16]0.004Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 21Table 4Multivariable associations between three derivations of the index (deciles, quintiles and quartiles) for place of soliciting and place of servicing clients andexchanging sex while high and exchanging sex for drugsExchanging sex while highExchanging sex for drugsAORs [95%CIs]PAORs [95%CIs]PPlace ofsolicitationDeciles1.01 [0.99–1.04]10.2651.01 [0.99–1.03]20.251Quintiles1.03 [0.98–1.09]30.2601.03 [0.98–1.07]40.237Quartiles1.05 [0.97–1.13]50.2341.04 [0.98–1.10]60.253Place ofservicingclientsDeciles1.01 [0.98–1.04]70.5361.03 [1.00–1.05]80.020Quintiles1.01 [0.96–1.07]90.6681.06 [1.01–1.10]100.021Quartiles1.01 [0.94–1.10]110.7441.09 [1.02–1.16]120.0091 Adjusted for: Migrant status, age, police harassment without arrest;2 Age, homeless, migrant status;3 Age, sexual minority, Aboriginal status, homeless, migrant status;4 Age, homeless, migrant status, police harassment without arrest;5 Age, sexual minority, Aboriginal status, homeless, migrant status;6 Age, homeless, migrant status;7 Age, sexual minority, Aboriginal status, homeless, migrant status, police harassment without arrest;8 Homeless, migrant status;9 Age, sexual minority, Aboriginal status, homeless, migrant status, police harassment without arrest;10Homeless, migrant status, police harassment without arrest;11sexual minority, Aboriginal status, homeless, migrant status, police harassment without arrest;12Homeless, migrant status, police harassment without arrestInt J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 22Table 5(a) Multivariable associations between each built environment indicator (place of solicitation) and exchangingsex while high and exchanging sex for drugs in the last six months; (b) Multivariable associations betweeneach individual built environment indicator and exchanging sex while high and exchanging sex for drugs,adjusting for police harassment(a)Environmental/land use variable Exchanged sex while high Exchanged sex for drugsAOR [95%CIs] P AOR [95%CIs] PLength of major roads within 50m buffer 1.05 [0.77–1.45]1 0.751 0.89 [0.69–1.14]2 0.346Length of alley roads within 50m buffer ns ns% Commercial areas within 50m buffer 0.76 [0.59–0.99]3 0.044 ns% Industrial areas within 50m buffer 1.14 [0.83–1.56]4 0.421 ns% of Parks within 50m buffer 1.18 [0.82–1.70]5 0.387 1.36 [1.06–1.75]6 0.017Count of lighting within 50m buffer ns ns% Built environment within 50m buffer ns ns(b)Environmental/land use variable Exchanged sex while high Exchanged sex for drugsAOR [95%CIs] P AOR [95%CIs] PLength of major roads within 50m buffer ns nsLength of alley roads within 50m buffer ns ns% Commercial areas within 50m buffer 0.86 [0.65–1.13]1 0.272 ns% Industrial areas within 50m buffer ns ns% of Parks within 50m buffer ns 1.38 [1.07–1.78]2 0.013Count of lighting within 50m buffer ns ns% Built environment within 50m buffer ns ns1Adjusted for: Age, age at first sex work, sexual minority, Aboriginal status, migrant status, homeless;2Age, migrant status;3Age, age at first sex work, Aboriginal status;4Sexual minority, migrant status, homeless;5Age, age at first sex work, migrant status, homeless;6Age, migrant status, homelessns = not significant in bivariate analysis and thus not explored in multivariable analysis1Adjusted for: Age at first sex work, sexual minority, migrant status, homeless, police harassment without arrest;2age, migrant status, homeless, police harassment without arrestns = not significant in bivariate analysis and thus not explored in multivariable analysis; or not significant in multivariable analysis in Table 5a,without adjusting for police harassment and thus not explored in multivariable analysis adjusting for police harassmentnc = police harassment not identified as a key confounder and thus not explored in multivariable analysisInt J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 23Table 6(a) Multivariable associations between each built environment indicator (place of servicing) and exchangingsex while high and exchanging sex for drugs in the last six months; (b) Multivariable associations betweeneach individual built environment indicator and exchanging sex while high and exchanging sex for drugs,adjusting for police harassment(a)Environmental/land use variable Exchanged sex while high Exchanged sex for drugsAOR [95%CIs] P AOR [95%CIs] PLength of major roads within 50m buffer ns 0.84 [0.66–1.06]1 0.144Length of alley roads within 50m buffer 0.69 [0.53–0.89]2 0.005% Commercial areas within 50m buffer 0.82 [0.64–1.06]3 0.130 0.72 [0.57–0.92]4 0.007% Industrial areas within 50m buffer 1.31 [1.00–1.71]5 0.051% of Parks within 50m buffer 1.08 [0.77–1.51]6 0.662 1.58 [1.14–2.18]7 0.006Count of lighting within 50m buffer ns 0.73 [0.56–0.93]8 0.012% Built environment within 50m buffer ns 0.75 [0.60–0.95]9 0.017(b)Environmental/land use variable Exchanged sex while high Exchanged sex for drugsAOR [95%CIs] P AOR [95%CIs] PLength of major roads within 50m buffer ns nsLength of alley roads within 50m buffer nc ns% Commercial areas within 50m buffer ns 0.74 [0.58–0.93]1 0.012% Industrial areas within 50m buffer ns ns% of Parks within 50m buffer ns ncCount of lighting within 50m buffer ns nc% Built environment within 50m buffer ns 0.76 [0.60–0.97]2 0.0251Adjusted for: Age, migrant status, homeless;2Migrant status, homeless;3Age, sexual minority, Aboriginal status, homeless;4Migrant status, homeless;5Aboriginal status, homeless;6Age, age at first sex work, Aboriginal status, migrant status, homeless;7Migrant status;8Migrant status;9Migrant status, homelessns = not significant in bivariate analysis and thus not explored in multivariable analysis1Adjusted for: Aboriginal status, homeless, police harassment without arrest;Int J Drug Policy. Author manuscript; available in PMC 2015 May 01.NIH-PA Author ManuscriptNIH-PA Author ManuscriptNIH-PA Author ManuscriptDeering et al. Page 242Migrant status, homeless, police harassment without arrestns = not significant in bivariate analysis and thus not explored in multivariable analysis; or not significant in multivariable analysis in Table 5a,without adjusting for police harassment and thus not explored in multivariable analysis adjusting for police harassmentnc = police harassment not identified as a key confounder and thus not explored in multivariable analysisInt J Drug Policy. Author manuscript; available in PMC 2015 May 01.

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