Social and structural factors associated with substance use within the support network of adults living in precarious housing in a socially marginalized neighborhood of Vancouver, Canada

Autoři: Verena Knerich aff001;  Andrea A. Jones aff002;  Sam Seyedin aff002;  Christopher Siu aff002;  Louie Dinh aff003;  Sara Mostafavi aff004;  Alasdair M. Barr aff006;  William J. Panenka aff002;  Allen E. Thornton aff007;  William G. Honer aff002;  Alexander R. Rutherford aff008
Působiště autorů: Departments of Computer Science, and Cultural Anthropology, Ludwig-Maximilians University, Munich, Germany aff001;  Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada aff002;  Department of Computer Science, University of British Columbia, Vancouver, BC, Canada aff003;  Department of Statistics, University of British Columbia, Vancouver, BC, Canada aff004;  Medical Genetics, Department Office, University of British Columbia, Vancouver, BC, Canada aff005;  Department of Anesthesia, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada aff006;  Department of Psychology, Simon Fraser University, Burnaby, BC, Canada aff007;  Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada aff008
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0222611



The structure of a social network as well as peer behaviours are thought to affect personal substance use. Where substance use may create health risks, understanding the contribution of social networks to substance use may be valuable for the design and implementation of harm reduction or other interventions. We examined the social support network of people living in precarious housing in a socially marginalized neighborhood of Vancouver, and analysed associations between social network structure, personal substance use, and supporters’ substance use.


An ongoing, longitudinal study recruited 246 participants from four single room occupancy hotels, with 201 providing social network information aligned with a 6-month observation period. Use of tobacco, alcohol, cannabis, cocaine (crack and powder), methamphetamine, and heroin was recorded at monthly visits. Ego- and graph-level measures were calculated; the dispersion and prevalence of substances in the network was described. Logistic mixed effects models were used to estimate the association between ego substance use and peer substance use. Permutation analysis was done to test for randomness of substance use dispersion on the social network.


The network topology corresponded to residence (Hotel) with two clusters differing in demographic characteristics (Cluster 1 –Hotel A: 94% of members, Cluster 2 –Hotel B: 95% of members). Dispersion of substance use across the network demonstrated differences according to network topology and specific substance. Methamphetamine use (overall 12%) was almost entirely limited to Cluster 1, and absent from Cluster 2. Different patterns were observed for other substances. Overall, ego substance use did not differ over the six-month period of observation. Ego heroin, cannabis, or crack cocaine use was associated with alter use of the same substances. Ego methamphetamine, powder cocaine, or alcohol use was not associated with alter use, with the exception for methamphetamine in a densely using part of the network. For alters using multiple substances, cannabis use was associated with lower ego heroin use, and lower ego crack cocaine use. Permutation analysis also provided evidence that dispersion of substance use, and the association between ego and alter use was not random for all substances.


In a socially marginalized neighborhood, social network topology was strongly influenced by residence, and in turn was associated with type(s) of substance use. Associations between personal use and supporter’s use of a substance differed across substances. These complex associations may merit consideration in the design of interventions to reduce risk and harms associated with substance use in people living in precarious housing.

Klíčová slova:

Behavior – Cannabis – Network analysis – Permutation – Social networks – Cocaine – Heroin – Neighborhoods


1. Aldridge RW, Story A, Hwang SW, Nordentoft M, Luchenski SA, Hartwell G, et al. Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. Lancet. 2018;391(10117): 241–250. doi: 10.1016/S0140-6736(17)31869-X 29137869

2. Luchenski S, Maguire N, Aldridge RW, Hayward A, Story A, Perri P, et al. What works in inclusion health: overview of effective interventions for marginalised and excluded populations. Lancet. 2018;391(10117): 266–280. doi: 10.1016/S0140-6736(17)31959-1 29137868

3. Vila-Rodriguez F, Panenka WJ, Lang DJ, Thornton AE, Vertinsky AT, Wong H, et al. The Hotel study: Multimorbidity in a community sample living in marginal housing. Am J Psychiatry. 2013;170(12): 1413–1422. doi: 10.1176/appi.ajp.2013.12111439 23929175

4. Honer WG, Cervantes-Larios A, Jones AA, Vila-Rodriguez F, Montaner JS, Tran H, et al. The Hotel study-clinical and health service effectiveness in a cohort of homeless or marginally housed persons. Can J Psychiatry. 2017;62(7): 482–492. doi: 10.1177/0706743717693781 28199798

5. Jones AA, Vila-Rodriguez F, Leonova O, Langheimer V, Lang DJ, Barr AM, et al. Mortality from treatable illnesses in marginally housed adults: a prospective cohort study. BMJ Open. 2015;5(8): e008876. doi: 10.1136/bmjopen-2015-008876 26297373

6. Deans GD, Raffa JD, Lai C, Fischer B, Krajden M, Amin J, et al. Mortality in a large community-based cohort of inner-city residents in Vancouver, Canada. CMAJ Open. 2013;1(2): E68–76. doi: 10.9778/cmajo.20130002 25077106

7. Marshall BDL, Milloy M-J, Wood E, Montaner JSG, Kerr T. Reduction in overdose mortality after the opening of North America's first medically supervised safer injecting facility: a retrospective population-based study. Lancet. 2011;377(9775): 1429–1437. doi: 10.1016/S0140-6736(10)62353-7 21497898

8. Bassel El N, Gilbert L, Wu E, Chang M. A social network profile and HIV risk among men on methadone: do social networks matter? JUrban Health 2006;83(4): 602–613.

9. Bertholet N, Faouzi M, Studer J, Daeppen J-B, Gmel G. Perception of tobacco, cannabis, and alcohol use of others is associated with one's own use. Addict Sci Clin Practice. 2013;8: 15.

10. Christakis NA, Fowler JH. Social contagion theory: examining dynamic social networks and human behavior. Stat Med. 2013;32(4): 556–577. doi: 10.1002/sim.5408 22711416

11. Lakon CM, Ennett ST, Norton EC. Mechanisms through which drug, sex partner, and friendship network characteristics relate to risky needle use among high risk youth and young adults. Soc Sci Med. 2006;63(9): 2489–2499. doi: 10.1016/j.socscimed.2006.06.015 16875770

12. Rosenquist JN, Murabito J, Fowler JH, Christakis NA. The spread of alcohol consumption in a large social network. Ann Intern Med. 2010;152(7): 426–W141. doi: 10.7326/0003-4819-152-7-201004060-00007 20368648

13. Stone A, Jason LA, Light JM, Stevens EB. The role of ego networks in studies of substance use disorder. Alcoholism Treatment Quarterly. 2016;34(3): 315–328. doi: 10.1080/07347324.2016.1182818 27594761

14. Valente TW, Gallaher P, Mouttapa M. Using social networks to understand and prevent substance use: a transdisciplinary perspective. Substance Use & Misuse. 2004;39(10–12): 1685–1712.

15. Barman-Adhikari A, Rice E, Winetrobe H, Petering R. Social network correlates of methamphetamine, heroin, and cocaine use in a sociometric network of homeless youth. Journal of the Society for Social Work and Research. 2015;6(3): 433–457.

16. Melander LA, Tyler KA, Schmitz RM. An inside look at homeless youths’ social networks: perceptions of substance use norms. Journal of Child & Adolescent Substance Use. 2016;25(1): 78–88.

17. Rice E, Barman-Adhikari A, Milbum NG, Monro W. Position-specific HIV risk in a large network of homeless youth. Am J Public Health. 2012;102(1): 141–147. doi: 10.2105/AJPH.2011.300295 22095350

18. Rice E, Rhoades H. How should network-based prevention for homeless youth be implemented? Addiction. 2013;108(9): 1625–1626. doi: 10.1111/add.12255 23947732

19. Schroeder JR, Latkin CA, Hoover DR, Curry AD, Knowlton AR, Celentano DD. Illicit drug use in one’s social network and in one’s neighbourhood predicts individual heroin and cocaine use. Ann Epidemiol. 2001;11(6): 389–394. 11454498

20. Tracy EM, Min MO, Park H, Jun M, Brown S, Francis MW. Personal network structure and substance use in women 12 months post treatment intake. J Subst Abuse Treat. 2016;62: 55–61. doi: 10.1016/j.jsat.2015.11.002 26712040

21. Latkin CA, Tseng T-Y, Davey-Rothwell M, Kennedy RD, Moran MB, Czaplicki L, et al. The relationship between neighborhood disorder, social networks, and indoor cigarette smoking among impoverished inner-city residents. J Urban Health 2017;94(4): 534–541. doi: 10.1007/s11524-017-0170-1 28560613

22. Gruenewald PJ, Ponicki WR, Remer LG, Waller LA, Zhu L, Gorman DM. Mapping the spread of methamphetamine abuse in California from 1995 to 2008. Am J Public Health. 2013;103(7): 1262–1270. doi: 10.2105/AJPH.2012.300779 23078474

23. Duncan GJ, Boisjoly J, Kremer M, Levy DM, Eccles J. Peer effects in drug use and sex among college students. J Abnorm Child Psychol. 2005;33(3): 375–385. 15957564

24. Mason M, Cheung I, Walker L. Substance use, social networks, and the geography of urban adolescents. Substance Use & Misuse. 2004;39(10–12): 1751–1777.

25. Tobin KE, Latkin CA, Curriero FC. An examination of places where African American men who have sex with men (MSM) use drugs/drink alcohol: a focus on social and spatial characteristics. Int J Drug Policy. 2014;25(3): 591–597. doi: 10.1016/j.drugpo.2013.12.006 24484732

26. Latkin CA, German D, Vlahov D, Galea S. Neighborhoods and HIV: a social ecological approach to prevention and care. Am Psychol. 2013;68(4): 210–224. doi: 10.1037/a0032704 23688089

27. Miller WC, Hoffman IF, Hanscom BS, Ha TV, Dumchev K, Djoerban Z, et al. A scalable, integrated intervention to engage people who inject drugs in HIV care and medication-assisted treatment (HPTN 074): a randomised, controlled phase 3 feasibility and efficacy study. Lancet. 2018;392(10149): 747–59. doi: 10.1016/S0140-6736(18)31487-9 30191830

28. Goehl L, Nunes E, Quitkin F, Hilton I. Social networks and methadone treatment outcome: the costs and benefits of social ties. Am J Drug Alc Abuse. 1993;19(3): 251–262.

29. Valente T. Social network influences on adolescent substance use: An introduction. Connections. 2003;25: 11–16.

30. Dombrowski K, Curtis R, Friedman S, Khan B. Topological and historical considerations for infectious disease transmission among injecting drug users in Bushwick, Brooklyn (USA). World J AIDS. 2013;3(1): 1–9. doi: 10.4236/wja.2013.31001 24672745

31. Ferrence R. Diffusion theory and drug use. Addiction. 2001;96(1): 165–173. doi: 10.1046/j.1360-0443.2001.96116512.x 11177527

32. Valente TW. Network interventions. Science. 2012;337(6090): 49–53. doi: 10.1126/science.1217330 22767921

33. McDonald LJ, Griffin ML, Kolodziej ME, Fitzmaurice GM, Weiss RD. The impact of drug use in social networks of patients with substance use and bipolar disorders. Am J Addict. 2011;20(2): 100–105. doi: 10.1111/j.1521-0391.2010.00117.x 21314751

34. Kelly JF, Stout RL, Greene MC, Slaymaker V. Young adults, social networks, and addiction recovery: post treatment changes in social ties and their role as a mediator of 12-step participation. PLOS ONE. 2014;9(6): e100121. doi: 10.1371/journal.pone.0100121 24945357

35. Bennett DA, Schneider JA, Buchman AS, Mendes de Leon C, Bienias JL, Wilson RS. The Rush Memory and Aging Project: study design and baseline characteristics of the study cohort. Neuroepidemiol. 2005;25(4): 163–175.

36. Bennett DA, Schneider JA, Tang Y, Arnold SE, Wilson RS. The effect of social networks on the relation between Alzheimer's disease pathology and level of cognitive function in old people: a longitudinal cohort study. Lancet Neurol. 2006;5(5): 406–412. doi: 10.1016/S1474-4422(06)70417-3 16632311

37. Gaetz S, Barr C, Friesen A, Harris B, Hill C, Kovacs-Burns K, et al. Canadian definition of homelessness. Canadian Observatory on Homelessness, Toronto. 2012. Available from:

38. Krausz M, Jang K. Lessons from the creation of Canada's poorest postal code. Lancet Psychiatry. 2015;2(3): e5. doi: 10.1016/S2215-0366(15)00045-0 26359906

39. Barrera M. A method for the assessment of social support networks in community survey research. Connections. 1980;3: 8–13.

40. Barrera M, Sandler IN, Ramsay TB. Preliminary development of a scale of social support: Studies on college students. Am J Comm Psychology. 1981;9(4): 435–447.

41. Jones AA, Vila-Rodriguez F, Panenka WJ, Leonova O, Strehlau V, Lang DJ, et al. Personalized risk assessment of drug-related harm is associated with health outcomes. PLOS ONE. 2013;8(11): e79754. doi: 10.1371/journal.pone.0079754 24223192

42. Cohen J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull. 1968;70(4): 213–220. 19673146

43. Friedman SR, Curtis R, Jose B, Neaigus A, Zenilman J, Culpepper-Morgan J, et al. Sex, drugs, and infections among youth. Parenterally and sexually transmitted diseases in a high-risk neighborhood. Sex Transm Dis. 1997;24(6): 322–326. doi: 10.1097/00007435-199707000-00003 9243738

44. Rothenberg RB, Woodhouse DE, Potterat JJ, Muth SQ, Darrow WW, Klovdahl AS. Social networks in disease transmission: the Colorado Springs Study. NIDA Res Monogr. 1995;151: 3–19. 8742758

45. Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal. Complex Systems. 2006: 1695.

46. Newman MEJ. Assortative mixing in networks. Phys Rev Lett. 2002;89(20): 208701. doi: 10.1103/PhysRevLett.89.208701 12443515

47. Fruchterman TMJ, Reingold EM. Graph drawing by force‐directed placement. Software: Practice and Experience. 1991;21(11): 1129–1164.

48. Wu L. Mixed Effects Models for Complex Data. Monographs on Statistics and Probability 113. 1st ed. Boca Raton: CRC Press; 2019.

49. Hastie T, Tibshirani R. Generalized additive models. Stat Sci. 1986;1: 297–310.

50. Bates DM. lme4: Mixed-effects modeling with R [Internet]. Available from:

51. Honer WG, Gewirtz G, Turey M. Psychosis and violence in cocaine smokers. Lancet. 1987;2(8556): 451.

52. Jones AA, Jang K, Panenka WJ, Barr AM, MacEwan GW, Thornton AE, et al. Rapid change in fentanyl prevalence in a community-based, high-risk sample. JAMA Psychiatry. 2018;75(3): 298–300. doi: 10.1001/jamapsychiatry.2017.4432 29387869

53. Rice E, Milburn NG, Monro W. Social networking technology, social network composition, and reductions in substance use among homeless adolescents. Prev Sci. 2011;12(1): 80–88. doi: 10.1007/s11121-010-0191-4 21194011

54. Bassel El N, Chen DR, Cooper D. Social support and social network profiles among women on methadone. Soc Serv Rev. 1998;72(3): 379–491.

55. Hurd YL. Cannabidiol: swinging the marijuana pendulum from “weed” to medication to treat the opioid epidemic. Trends Neurosci. 2017;40(3): 124–127. doi: 10.1016/j.tins.2016.12.006 28162799

56. Valente TW, Pitts SR. An appraisal of social network theory and analysis as applied to public health: challenges and opportunities. Ann Rev Pub Health. 2017;38(1): 103–118.

57. Latkin CA, Knowlton AR. Social network assessments and interventions for health behavior change: a critical review. Behav Med. 2015;41(3): 90–97. doi: 10.1080/08964289.2015.1034645 26332926

58. Christakis NA. Social networks and collateral health effects. BMJ. 2004;329(7459): 184–185. doi: 10.1136/bmj.329.7459.184 15271805

59. Min MO, Tracy EM, Kim H, Park H, Jun M, Brown S, et al. Changes in personal networks of women in residential and outpatient substance abuse treatment. J Subst Abuse Treat. 2013;45(4): 325–334. doi: 10.1016/j.jsat.2013.04.006 23755971

Článok vyšiel v časopise


2019 Číslo 9

Najčítanejšie v tomto čísle

Tejto téme sa ďalej venujú…


Zvýšte si kvalifikáciu online z pohodlia domova

Faktory ovlivňující léčbu levotyroxinem
nový kurz

Kurz originály vs. generika

Autori: MUDr. Petr Výborný, CSc., FEBO

Autori: MUDr. Jiří Horažďovský, Ph.D

Klinická farmakokinetika betablokátorů

Všetky kurzy
Zabudnuté heslo

Nemáte účet?  Registrujte sa

Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.


Nemáte účet?  Registrujte sa